Learners who want a structured route across connected courses
School of Data & AIBeginner to Intermediate
Data Analytics
Become a job-ready data analyst with practical tools and portfolio projects.
Learn Excel, SQL, Python, Power BI, dashboards, reporting, analytics thinking, and business storytelling so you can turn raw data into insights that support real decisions.
Target role
Data Analyst, BI Analyst
Duration
Flexible duration - Flexible weekly pace
Course sequence
6 courses
Support model
Choose your learning support level
Outcome
Built around a clear role target.
Data Analyst, BI Analyst
Course sequence
See how the courses build into the full path.
Each course has a focused job, but the value compounds when you follow the sequence, complete the projects, and use the support model around the full path.
School of Data & AIBeginner to Intermediate6 courses
Data Analytics
Become a practical data analyst who can clean, analyze, visualize, and communicate business data using Excel, SQL, Python, Power BI, and real-world analytics projects.
Target role
Data Analyst, BI Analyst
Duration
Flexible duration - Flexible weekly pace
Support
Choose your learning support level
1 Path only2 weeksBeginnerData Foundations
Build the essential foundation for working with data, understanding business problems, and preparing for tools like Excel, SQL, Python, Power BI, machine learning, AI, and data engineering.
Understand how data is used to solve real business problems.Available through the path so the work stays connected to the full outcome.Understand how data is used to solve real business problems.Explain the difference between data, reports, dashboards, insights, and decisions.Understand the major roles across analytics, data science, AI, and data engineering.Identify common tools used by modern data teams.View course outline2 Standalone + path6 weeksBeginner to IntermediateExcel for Data Analytics
Master the Excel skills used by data analysts to clean, organize, calculate, summarize, visualize, and report business data with confidence.
Clean and organize messy spreadsheet data.Can be started alone, then compounded inside the full path.Clean and organize messy spreadsheet data.Use essential Excel formulas for analysis and reporting.Apply lookup functions to connect and enrich datasets.Build pivot tables for fast business summaries.View course3 Standalone + path8 weeksIntermediatePower BI for Business Intelligence
Learn to connect, clean, model, measure, visualize, and present business data using Power BI.
Connect Power BI to different data sources.Can be started alone, then compounded inside the full path.Connect Power BI to different data sources.Clean and transform data using Power Query.Build effective data models and table relationships.Write DAX measures for business reporting.View course4 Standalone + path7 weeksBeginner to IntermediateSQL for Data Analytics
Learn the SQL skills data analysts use to extract, filter, join, group, and analyze data from relational databases.
Understand tables, columns, rows, keys, and relationships.Can be started alone, then compounded inside the full path.Understand tables, columns, rows, keys, and relationships.Write SQL queries to retrieve business data.Filter, sort, and structure query results.Join data across multiple tables correctly.View course5 Standalone + path8 weeksBeginner to IntermediatePython for Data Analytics
Learn Python for real analytics work: data cleaning, exploration, transformation, automation, and visual insight generation.
Write Python code for data analysis tasks.Can be started alone, then compounded inside the full path.Write Python code for data analysis tasks.Use notebooks for structured exploratory analysis.Import CSV, Excel, and structured data files.Clean missing, duplicated, inconsistent, and messy data.View course6 Path only6 weeksIntermediateData Analytics Studio
Apply Excel, SQL, Python, Power BI, and storytelling to complete end-to-end analytics projects for your portfolio.
Translate business problems into clear analytics questions.Available through the path so the work stays connected to the full outcome.Translate business problems into clear analytics questions.Plan an end-to-end analytics project.Choose the right tool for each stage of analysis.Clean, query, analyze, visualize, and present real datasets.View course outline
Curriculum
Follow the courses in sequence.
The path moves toward Data Analyst, BI Analyst through complete course outlines, from phases and modules down to lesson page topics.
1Beginner2 weeksPath onlyData FoundationsBuild the essential foundation for working with data, understanding business problems, and preparing for tools like Excel, SQL, Python, Power BI, machine learning, AI, and data engineering.6 phases7 modules28 lessons88 pages
1Phase 1 - Introduction to Data & AIIntroduce data, organizational data use, and the modern data ecosystem.1 modules3 lessons1 week
Module 1: The World of DataUnderstand what data is, how organizations use it, and how the modern data ecosystem works.3 lessons
Lesson 1: What Is Data?Understand data as recorded facts, observations, events, and signals that can be interpreted to support decisions.75 minarticle5 pages
Welcome and Learning Objectives
Start the lesson and understand the purpose of learning data foundations.
8 min
Data in Plain English
Explain what data is and why context matters.
15 min
Structured, Semi-Structured, and Unstructured Data
Classify the main forms of data students will meet in analytics, data science, AI, and data engineering.
18 min
Data Sources in Everyday Life
Help students see that data is created constantly by normal activities.
15 min
Exercise - Daily Data Source Audit
Students identify real data sources around them and classify them.
19 min
Lesson 2: How Organizations Use DataExplore how businesses and institutions use data for decisions, reporting, forecasting, optimization, and automation.80 minarticle5 pages
Welcome and Learning Objectives
Introduce organizational data use.
8 min
The Five Common Uses of Data
Explain common ways data supports organizations.
22 min
Case Study - Netflix Recommendations
Introduce recommendations as a beginner-friendly example of organizational data use.
20 min
Data Usage Map
Show how one organization can use many kinds of data.
15 min
Exercise - Company Data Usage Map
Students map how data may be used in a real organization.
15 min
Lesson 3: The Modern Data EcosystemUnderstand how data moves from sources into databases, warehouses, dashboards, models, AI systems, and decisions.80 minarticle5 pages
Welcome and Learning Objectives
Introduce the modern data ecosystem.
8 min
The Main Components
Explain core components in the ecosystem.
22 min
Complete Data Flow Example
Show a realistic beginner-friendly data flow.
20 min
Diagram Exercise - Draw Complete Data Flow
Students create a data ecosystem diagram.
20 min
Module Summary
Summarize the first module and prepare students for data roles.
10 min
2Phase 2 - Data Careers & RolesHelp students understand the major data and AI career paths before choosing a specialization.1 modules5 lessons1 week
Module 1: Understanding the Data ProfessionCompare the responsibilities, deliverables, tools, and thinking patterns across modern data roles.5 lessons
Lesson 1: Data AnalystUnderstand what data analysts do, the problems they solve, and the deliverables they create.45 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
22 min
Practice Activity
Apply the concept through a guided activity.
15 min
Lesson 2: Data ScientistUnderstand how data scientists use statistics, programming, and models to explore patterns and make predictions.45 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
22 min
Practice Activity
Apply the concept through a guided activity.
15 min
Lesson 3: Data EngineerUnderstand how data engineers build pipelines, warehouses, and infrastructure that make data usable.45 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
22 min
Practice Activity
Apply the concept through a guided activity.
15 min
Lesson 4: AI EngineerUnderstand AI engineering at a high level, including LLMs, RAG, agents, and AI product systems.45 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
22 min
Practice Activity
Apply the concept through a guided activity.
15 min
Lesson 5: Choosing Your PathUse a practical decision framework to choose a data or AI learning path.60 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
30 min
Practice Activity
Apply the concept through a guided activity.
22 min
3Phase 3 - Data ThinkingTeach students how to ask better questions, define useful metrics, investigate causes, and communicate insights.1 modules4 lessons1 week
Module 1: Analytical ThinkingBuild the thinking habits that separate tool users from real data professionals.4 lessons
Lesson 1: Questions Before AnswersLearn to define problems and ask useful analytical questions before touching tools.50 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
25 min
Practice Activity
Apply the concept through a guided activity.
17 min
Lesson 2: Metrics and KPIsUnderstand metrics, KPIs, vanity metrics, and actionable measures.55 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
27 min
Practice Activity
Apply the concept through a guided activity.
20 min
Lesson 3: Root Cause AnalysisLearn how to investigate business problems instead of jumping to shallow conclusions.55 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
27 min
Practice Activity
Apply the concept through a guided activity.
20 min
Lesson 4: Data StorytellingLearn how to communicate insights through clear narratives and decision-focused reporting.55 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
27 min
Practice Activity
Apply the concept through a guided activity.
20 min
4Phase 4 - Working with DataDevelop core data literacy: data types, data quality, cleaning concepts, and exploratory analysis.1 modules4 lessons1 week
Module 1: Data LiteracyUnderstand datasets, quality issues, cleaning concepts, and beginner exploration.4 lessons
Lesson 1: Data TypesClassify numeric, categorical, time-series, and text data.45 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
22 min
Practice Activity
Apply the concept through a guided activity.
15 min
Lesson 2: Data QualityIdentify missing values, duplicates, inconsistencies, and their business impact.50 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
25 min
Practice Activity
Apply the concept through a guided activity.
17 min
Lesson 3: Data Cleaning ConceptsUnderstand validation, standardization, and transformation at a beginner level.50 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
25 min
Practice Activity
Apply the concept through a guided activity.
17 min
Lesson 4: Exploratory AnalysisLearn how to explore patterns, trends, outliers, and initial questions in a dataset.55 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
27 min
Practice Activity
Apply the concept through a guided activity.
20 min
5Phase 5 - Statistics for Decision MakingTeach practical, business-focused statistics without heavy mathematics.1 modules4 lessons1 week
Module 1: Practical StatisticsUse basic statistics to summarize data and support better decisions.4 lessons
Lesson 1: Descriptive StatisticsUnderstand mean, median, mode, variance, and how they describe business data.50 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
25 min
Practice Activity
Apply the concept through a guided activity.
17 min
Lesson 2: Probability ConceptsUnderstand uncertainty, risk, and likelihood using business examples.45 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
22 min
Practice Activity
Apply the concept through a guided activity.
15 min
Lesson 3: Correlation vs CausationAvoid common mistakes and misleading conclusions when variables move together.50 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
25 min
Practice Activity
Apply the concept through a guided activity.
17 min
Lesson 4: Making Decisions with DataUse confidence, evidence, and tradeoffs to make better business decisions.55 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
27 min
Practice Activity
Apply the concept through a guided activity.
20 min
6Phase 6 - Data, AI & EthicsIntroduce responsible data use, privacy, bias, AI ethics, and the future of data work.2 modules8 lessons1 week
Module 1: Responsible Data UseBuild responsible habits around privacy, bias, fairness, transparency, and AI accountability.4 lessons
Lesson 1: Data PrivacyUnderstand personal data, consent, and compliance concepts at a beginner level.45 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
22 min
Practice Activity
Apply the concept through a guided activity.
15 min
Lesson 2: Bias in DataUnderstand how bias, fairness, and representation affect data conclusions.50 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
25 min
Practice Activity
Apply the concept through a guided activity.
17 min
Lesson 3: AI EthicsUnderstand hallucinations, transparency, accountability, and safe AI usage.55 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
27 min
Practice Activity
Apply the concept through a guided activity.
20 min
Lesson 4: Future of Data and AIExplore AI transformation, automation, emerging careers, and personal roadmap planning.50 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
25 min
Practice Activity
Apply the concept through a guided activity.
17 min
Module 2: Foundations Projects and GraduationPackage learning into mini projects, a final foundations project, and graduation requirements.4 lessons
Lesson 1: Mini Project 1 - Business Metrics AnalysisAnalyze a business domain and design practical metrics and recommendations.60 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
30 min
Practice Activity
Apply the concept through a guided activity.
22 min
Lesson 2: Mini Project 2 - Data Quality AuditAudit a messy dataset and produce a quality report.60 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
30 min
Practice Activity
Apply the concept through a guided activity.
22 min
Lesson 3: Final Foundations Project - Data-Driven Business AnalysisAnalyze a real company or product from a data perspective and present recommendations.90 minarticle3 pages
Overview and Learning Objectives
Start the lesson and understand what the student should be able to do.
8 min
Concepts and Examples
Introduce the main concepts with practical examples.
45 min
Practice Activity
Apply the concept through a guided activity.
37 min
Lesson 4: Graduation Requirements and Portfolio OutcomeClarify what students must complete and what they should have in their portfolio.40 minarticle1 pages
Requirements and Portfolio Checklist
Summarize graduation requirements.
40 min
2Beginner to Intermediate6 weeksExcel for Data AnalyticsMaster the Excel skills used by data analysts to clean, organize, calculate, summarize, visualize, and report business data with confidence.8 phases8 modules34 lessons101 pages
1Phase 1 - Excel Foundations for AnalystsBuild the foundation for professional spreadsheet analytics: workflow, navigation, data entry, formatting, structure, and workbook design.1 modules4 lessons1–2 weeks
Module 1: Working with Data in ExcelLearn spreadsheet analytics, Excel navigation, reliable data entry, structured tables, validation, and professional workbook design.4 lessons
Lesson 1: Introduction to Spreadsheet AnalyticsUnderstand spreadsheet analytics, where Excel fits in the analyst workflow, and how analysts use workbooks to support decisions.75 minarticle5 pages
Welcome and Learning Objectives
Start the course and understand why Excel still matters for data analytics.
8 min
What Spreadsheet Analytics Is
Define spreadsheet analytics in practical business terms.
15 min
Common Business Use Cases
Show where Excel appears in real business work.
18 min
The Analyst Workflow
Teach the workflow students will repeat throughout the course.
18 min
Exercise - Sales Dataset Discovery Lab
Students explore a sales dataset and write first observations.
16 min
Lesson 2: Excel Interface and NavigationLearn the Excel workspace, workbook structure, sheets, navigation habits, and shortcuts that make analysis faster.70 minarticle4 pages
Welcome and Learning Objectives
Introduce the Excel interface and navigation habits.
8 min
Workbook and Worksheet Basics
Explain the basic objects students use in Excel.
15 min
Navigation and Shortcuts
Teach practical navigation habits.
20 min
Exercise - Workbook Navigation Challenge
Students practice navigating a multi-sheet workbook.
27 min
Lesson 3: Data Entry and FormattingLearn how data types, formatting, tables, and validation affect the quality of spreadsheet analysis.75 minarticle4 pages
Welcome and Learning Objectives
Introduce reliable data entry and formatting.
8 min
Data Types and Formatting
Explain how Excel data types affect analysis.
20 min
Tables and Data Validation
Introduce Excel tables and validation rules.
20 min
Exercise - Structured Dataset Build
Students create a clean dataset structure.
27 min
Lesson 4: Professional Spreadsheet DesignLearn layout principles, naming conventions, and documentation habits that make workbooks easier to trust and maintain.75 minarticle4 pages
Welcome and Learning Objectives
Introduce professional workbook design.
8 min
Workbook Layout Principles
Teach workbook organization.
20 min
Naming and Documentation
Explain naming conventions and documentation.
18 min
Exercise - Spreadsheet Rescue
Students redesign a poorly structured spreadsheet.
29 min
2Phase 2 - Core Analytical FunctionsBuild confidence with formulas and functions used in business reporting and data preparation.1 modules6 lessons2 weeks
Module 1: Formulas and FunctionsUse core formulas, logical functions, text/date functions, and lookup techniques for analysis.6 lessons
Lesson 1: Formula FundamentalsLearn references, relative references, absolute references, and basic calculations.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided exercise.
20 min
Lesson 2: Logical FunctionsUse IF, IFS, AND, and OR to encode business rules in Excel.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 3: Text FunctionsUse text functions to clean and prepare customer or product data.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided exercise.
20 min
Lesson 4: Date and Time FunctionsUse date and time functions for subscription and operational reporting.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided exercise.
20 min
Lesson 5: Lookup FunctionsUse lookup functions to match records and enrich reporting datasets.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided exercise.
25 min
Lesson 6: Mini Project 1 - Sales Reporting WorkbookBuild a sales reporting workbook using formulas, lookups, and structured calculations.80 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
3Phase 3 - Data Cleaning and PreparationLearn how to identify dirty data, clean it, validate it, and prepare it for analysis.1 modules5 lessons1–2 weeks
Module 1: Data Quality ManagementBuild practical data cleaning and quality management habits in Excel.5 lessons
Lesson 1: Understanding Dirty DataIdentify missing values, duplicates, inconsistencies, and the risks they create.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided exercise.
17 min
Lesson 2: Cleaning TechniquesApply practical cleanup techniques to customer and operational data.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 3: Data ValidationUse validation rules, dropdowns, and error prevention techniques.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided exercise.
20 min
Lesson 4: Data TransformationTransform datasets by splitting, combining, and restructuring fields.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 5: Mini Project 2 - Customer Data Cleanup ProjectClean a messy customer dataset and produce a data quality report.80 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
4Phase 4 - Analytical Thinking with ExcelUse Excel to analyze business data through filtering, formatting, descriptive statistics, trends, and scenarios.1 modules5 lessons1–2 weeks
Module 1: Data AnalysisMove from cleaned data to practical analysis and business interpretation.5 lessons
Lesson 1: Sorting and FilteringUse filters and sorting to investigate business performance.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided exercise.
17 min
Lesson 2: Conditional FormattingUse visual indicators to highlight trends, exceptions, and risks.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided exercise.
17 min
Lesson 3: Descriptive StatisticsUse basic statistics to summarize sales and performance data.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided exercise.
20 min
Lesson 4: Trend AnalysisAnalyze growth rates, comparisons, and time-based performance.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 5: Scenario AnalysisUse what-if analysis, Goal Seek, and scenarios for business forecasting.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
5Phase 5 - Pivot Tables and ReportingBuild professional reporting workflows with pivot tables, pivot charts, slicers, timelines, and interactive dashboards.1 modules5 lessons1–2 weeks
Module 1: Professional ReportingUse pivot tables and interactive reporting tools to summarize business data.5 lessons
Lesson 1: Pivot Tables FundamentalsCreate pivot tables for summarization, grouping, and reporting.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 2: Advanced Pivot TablesUse calculated fields and multi-level analysis for deeper reporting.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 3: Pivot ChartsTurn pivot summaries into visual executive reports.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided exercise.
20 min
Lesson 4: Interactive ReportingUse slicers, timelines, and filters to make reports interactive.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 5: Milestone Project - Business Performance DashboardBuild an interactive dashboard for business performance monitoring.100 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
6Phase 6 - Business Dashboards and StorytellingCreate clear visuals, design dashboards, and communicate insights to stakeholders.1 modules4 lessons1–2 weeks
Module 1: Data VisualizationUse charts, dashboard design, and storytelling to communicate business insights.4 lessons
Lesson 1: Choosing the Right ChartSelect appropriate charts for different business questions.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided exercise.
17 min
Lesson 2: Dashboard Design PrinciplesDesign dashboards with layout, hierarchy, simplicity, and clarity.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 3: Data StorytellingCommunicate insights, risks, opportunities, and recommendations.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided exercise.
20 min
Lesson 4: Building Executive DashboardsBuild KPI, operational, and management reporting dashboards.80 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
40 min
Practice Activity
Apply the lesson through a guided exercise.
32 min
7Phase 7 - Productivity and AutomationImprove speed, consistency, and repeatability with productivity techniques, macros, and reusable templates.1 modules3 lessons1 week
Module 1: Working EfficientlyAutomate repetitive work and create reusable reporting assets.3 lessons
Lesson 1: Advanced Productivity TechniquesUse keyboard shortcuts, named ranges, and dynamic formulas to work faster and reduce errors.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided exercise.
17 min
Lesson 2: Introduction to AutomationUnderstand recorded macros and workflow automation concepts.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
Lesson 3: Reusable Reporting TemplatesBuild templates that can be reused for weekly or monthly reporting.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided exercise.
22 min
8Phase 8 - Capstone, Graduation and PortfolioComplete an executive analytics dashboard capstone and package portfolio-ready Excel work.1 modules2 lessons1 week
Module 1: Executive Business Analytics CapstoneStudents complete an industry-based capstone project and prepare their portfolio outcome.2 lessons
Lesson 1: Final Capstone - Executive Business Analytics DashboardBuild a professional Excel analytics dashboard for one selected industry.140 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
Lesson 2: Graduation Requirements and Portfolio OutcomeClarify completion requirements and expected portfolio outputs.45 minarticle1 pages
Requirements and Portfolio Checklist
Summarize graduation requirements and portfolio assets.
45 min
3Intermediate8 weeksPower BI for Business IntelligenceLearn to connect, clean, model, measure, visualize, and present business data using Power BI.8 phases11 modules54 lessons163 pages
1Phase 1 - Business Intelligence FoundationsBuild BI thinking before dashboard building: BI concepts, Power BI ecosystem, BI analyst workflow, metrics, KPIs, and requirements documentation.1 modules5 lessons1–2 weeks
Module 1: Introduction to BI and Power BIUnderstand business intelligence, Power BI components, BI workflow, business metrics, and requirements gathering.5 lessons
Lesson 1: What Is Business Intelligence?Understand business intelligence, how it differs from analytics and reporting, and why organizations need dashboards.85 minarticle6 pages
Welcome and Learning Objectives
Start the course and understand the purpose of business intelligence.
8 min
BI in Plain English
Explain BI in practical language.
16 min
BI vs Reporting vs Data Analytics
Clarify the difference between common data terms.
20 min
Why Businesses Need Dashboards
Explain dashboard value in organizations.
18 min
Common BI Use Cases
Show BI use cases across departments.
18 min
Exercise - BI Use Case Discovery
Students identify BI use cases across business functions.
25 min
Lesson 2: Power BI EcosystemUnderstand the Power BI ecosystem: Desktop, Service, Mobile, Report Server, datasets, reports, dashboards, and workspaces.85 minarticle5 pages
Welcome and Learning Objectives
Introduce the Power BI ecosystem.
8 min
Power BI Components
Explain the major Power BI components.
22 min
Datasets, Reports, Dashboards and Workspaces
Explain common Power BI objects.
22 min
Interface Exploration
Guide students through Power BI interface areas.
18 min
Exercise - Power BI Interface Map
Students identify major components in the Power BI interface.
15 min
Lesson 3: BI Analyst WorkflowMap a BI project workflow from business question to data connection, cleaning, modeling, DAX, dashboard design, publishing, and feedback.85 minarticle5 pages
Welcome and Learning Objectives
Introduce the BI project workflow.
8 min
From Business Question to Dashboard
Explain the BI workflow.
24 min
Requirements Gathering
Explain stakeholder and KPI requirements.
20 min
Feedback and Iteration
Explain dashboard improvement after publishing.
18 min
Exercise - BI Project Workflow Map
Students map a BI project workflow from question to dashboard.
15 min
Lesson 4: Understanding Business MetricsUnderstand KPIs, metrics vs dimensions, leading vs lagging indicators, vanity metrics, actionable metrics, and dashboard-ready KPI design.85 minarticle5 pages
Welcome and Learning Objectives
Introduce metrics and KPI thinking.
8 min
Metrics, KPIs and Dimensions
Explain metric concepts for BI.
22 min
Leading, Lagging, Vanity and Actionable Metrics
Explain better KPI judgment.
22 min
E-Commerce KPI Framework
Show a practical KPI design example.
20 min
Exercise - E-Commerce KPI Design Studio
Students design dashboard KPIs for an e-commerce business.
13 min
Lesson 5: Mini Project 1 - BI Requirements DocumentCreate a BI requirements document for a selected business domain before building any dashboard.90 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
2Phase 2 - Data Connection and Power QueryConnect to data sources and use Power Query to clean, transform, combine, and prepare model-ready tables.2 modules10 lessons2 weeks
Module 1: Connecting to Data SourcesConnect Power BI to files, databases, web/cloud sources, and choose the right source strategy.4 lessons
Lesson 1: Importing FilesImport Excel files, CSV files, folder imports, and understand data source settings and refresh concepts.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
20 min
Lesson 2: Connecting to DatabasesUnderstand SQL database connection concepts, Import mode, DirectQuery overview, and query folding basics.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 3: Connecting to Web and Cloud SourcesConnect to web data, SharePoint/OneDrive concepts, cloud data sources, and refresh considerations.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
20 min
Lesson 4: Data Source StrategyChoose the right data source based on ownership, refresh frequency, reliability, and reporting risks.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Module 2: Data Cleaning with Power QueryUse Power Query for cleaning, transformation, combination, and reusable preparation pipelines.6 lessons
Lesson 1: Power Query FundamentalsUnderstand Query Editor, applied steps, data preview, data types, and column renaming.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 2: Cleaning Messy DataRemove duplicates, handle missing values, trim text, standardize categories, and replace values.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
25 min
Lesson 3: Transforming DataSplit columns, merge columns, extract values, create conditional columns, and custom columns.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
25 min
Lesson 4: Combining DataAppend queries, merge queries, use join types, and apply relationship logic.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 5: Power Query Best PracticesUse step naming, query organization, data type discipline, reusable transformations, and avoid fragile reports.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 6: Mini Project 2 - Data Preparation PipelinePrepare messy business data into clean model-ready tables using Power Query.100 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
3Phase 3 - Data Modeling for BIBuild accurate BI models using facts, dimensions, relationships, star schema, and date tables.1 modules6 lessons1–2 weeks
Module 1: Data Modeling FundamentalsModel business data correctly for reliable reporting and reusable dashboards.6 lessons
Lesson 1: Why Data Modeling MattersUnderstand flat tables vs data models, reporting accuracy, performance, reusability, and business definitions.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
20 min
Lesson 2: Fact and Dimension TablesClassify facts, dimensions, measures, granularity, transaction data, and lookup tables.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
25 min
Lesson 3: RelationshipsBuild one-to-many, many-to-one, manage many-to-many risks, cross-filter direction, active and inactive relationships.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
25 min
Lesson 4: Star SchemaUse star schema with sales fact table, date, product, customer, and region dimensions.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 5: Date TablesCreate and connect date tables for calendar and fiscal reporting and time intelligence preparation.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 6: Milestone Project 1 - Sales BI Data ModelBuild a documented Power BI sales data model.100 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
4Phase 4 - DAX for Business IntelligenceWrite practical DAX measures for KPIs, filtering, ratios, time intelligence, ranking, segmentation, and dynamic reporting.2 modules11 lessons2 weeks
Module 1: DAX FundamentalsBuild practical DAX foundations for business KPI reporting.5 lessons
Lesson 1: Introduction to DAXUnderstand calculated columns vs measures, row context, filter context, and why DAX is different from Excel formulas.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 2: Core Aggregation MeasuresUse SUM, COUNT, DISTINCTCOUNT, AVERAGE, MIN, and MAX.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 3: CALCULATEUnderstand why CALCULATE matters and how it modifies filter context.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 4: DAX with FiltersUse FILTER, ALL, VALUES, SELECTEDVALUE, and DIVIDE for percentages and ratios.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 5: Business KPI MeasuresCreate practical KPI measures for total revenue, profit, margin, AOV, conversion concepts, and customer count.75 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
37 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
30 min
Module 2: Time Intelligence and Advanced DAXUse time intelligence, growth, ranking, segmentation, dynamic measures, and DAX debugging practices.6 lessons
Lesson 1: Time Intelligence BasicsCreate year-to-date, month-to-date, quarter-to-date, previous period, and period comparison measures.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 2: Growth AnalysisCalculate month-over-month growth, year-over-year growth, percentage change, and interpret trends.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
25 min
Lesson 3: Ranking and SegmentationUse RANKX, Top-N analysis, and customer/product segmentation.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
25 min
Lesson 4: Dynamic MeasuresUse SWITCH, dynamic KPI selection, and parameter-style reporting.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 5: DAX Debugging and Best PracticesOrganize measures, use naming conventions, debug wrong totals, and avoid over-complex DAX.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
25 min
Lesson 6: Milestone Project 2 - Executive KPI Measure LibraryBuild a documented DAX measure library for executive reporting.100 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
5Phase 5 - Dashboard Design and Data StorytellingDesign decision-focused dashboards and communicate insights through executive, diagnostic, and operational report pages.2 modules10 lessons2 weeks
Module 1: Dashboard Design PrinciplesApply dashboard UX, chart selection, interactivity, readability, and accessibility principles.5 lessons
Lesson 1: Designing for Decision MakersDesign dashboards for audience, decision context, executive vs operational use, and reduced noise.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 2: Choosing the Right VisualMatch visuals to business questions using bars, lines, cards, tables, matrices, maps, decomposition tree, and waterfall charts.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
25 min
Lesson 3: Dashboard Layout and UXUse visual hierarchy, spacing, alignment, color discipline, typography, and navigation.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 4: InteractivityUse slicers, filters, drill-through, tooltips, bookmarks, and buttons.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 5: Accessibility and ReadabilityImprove contrast, labels, clutter, executive readability, and mobile readability.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Module 2: Business Storytelling with DashboardsTurn visuals into insight narratives and build executive, diagnostic, and operational report pages.5 lessons
Lesson 1: From Charts to InsightsWrite insight statements with context, explanation, and recommendation.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
20 min
Lesson 2: Executive Summary PagesBuild executive pages using KPI cards, key trends, alerts, action areas, and management reporting.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 3: Diagnostic Dashboard PagesDesign root-cause analysis, drill-down flow, segmentation, and investigation pages.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 4: Operational Dashboard PagesBuild monitoring workflows, exception reporting, daily/weekly usage, and performance tracking pages.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 5: Project - Sales Performance DashboardBuild a multi-page sales performance dashboard.110 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
6Phase 6 - Power BI Service, Sharing and GovernancePublish, refresh, share, secure, and govern Power BI reports professionally.1 modules5 lessons1–2 weeks
Module 1: Publishing and CollaborationUse Power BI Service concepts for publishing, refresh, access control, RLS, and governance.5 lessons
Lesson 1: Publishing ReportsUnderstand Power BI Service, workspaces, publishing workflow, and dataset/report relationship.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 2: Refresh and Scheduled UpdatesUnderstand manual refresh, scheduled refresh, gateway concepts, and refresh failure risks.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 3: Sharing and Access ControlUnderstand apps, sharing reports, permissions, workspace roles, and RLS overview.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
Lesson 4: Row-Level SecurityImplement role-based filtering and test as roles.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 5: Governance BasicsUse certified datasets, report versioning, documentation, naming standards, and data ownership.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
22 min
7Phase 7 - Real-World BI ScenariosBuild BI dashboard pages for sales, finance, marketing, operations, HR, and education domains.1 modules5 lessons1–2 weeks
Module 1: Business Domain DashboardsApply BI skills to common business dashboard scenarios.5 lessons
Lesson 1: Sales Analytics DashboardBuild sales analysis pages for revenue, targets, customers, and products.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 2: Finance DashboardBuild finance reporting pages for revenue, expenses, profit, and budget vs actual.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 3: Marketing DashboardBuild marketing dashboard pages for leads, campaigns, conversion, and CAC concepts.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 4: Operations DashboardBuild operations pages for SLA, throughput, delays, and process bottlenecks.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
Lesson 5: HR or Education DashboardBuild people or education analytics pages for attendance, completion, engagement, and performance.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Power BI exercise.
27 min
8Phase 8 - Capstone, Graduation and PortfolioComplete an end-to-end Power BI BI capstone and package portfolio-ready BI assets.1 modules2 lessons1 week
Module 1: End-to-End Power BI CapstoneStudents complete an industry-based Power BI dashboard project from requirements to presentation.2 lessons
Lesson 1: Final Capstone - End-to-End Power BI Business Intelligence ProjectBuild a professional Power BI BI project for one selected industry.170 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
Lesson 2: Graduation Requirements and Portfolio OutcomeClarify completion requirements and expected portfolio outputs.45 minarticle1 pages
Requirements and Portfolio Checklist
Summarize graduation requirements and portfolio assets.
45 min
4Beginner to Intermediate7 weeksSQL for Data AnalyticsLearn the SQL skills data analysts use to extract, filter, join, group, and analyze data from relational databases.8 phases8 modules36 lessons107 pages
1Phase 1 - Relational Database FoundationsBuild database thinking before writing SQL: files vs databases, tables, records, relationships, primary keys, foreign keys, and basic data modeling.1 modules5 lessons1–2 weeks
Module 1: Understanding Data and DatabasesUnderstand why databases exist and how relational database structures support business analytics.5 lessons
Lesson 1: Why Databases ExistUnderstand why databases exist, how they differ from files, and why SQL matters for business analytics.75 minarticle5 pages
Welcome and Learning Objectives
Start the course and understand why databases matter.
8 min
Files vs Databases
Explain the difference between files and databases.
16 min
Business Data and Structured Data
Introduce business data and structured records.
17 min
Relational Databases in Plain English
Introduce relational databases and why they matter.
18 min
Exercise - Application Database Discovery
Students identify databases behind common applications.
16 min
Lesson 2: Database FundamentalsUnderstand tables, rows, columns, and records — the foundation of relational database thinking.75 minarticle5 pages
Welcome and Learning Objectives
Introduce the basic building blocks of databases.
8 min
Tables, Rows, Columns and Records
Explain core database structure.
18 min
From Business Entity to Table
Show how real business objects become database tables.
18 min
Design a Simple Customer Database
Guide students through customer table design.
18 min
Exercise - Customer Database Blueprint
Students submit a simple customer database design.
13 min
Lesson 3: RelationshipsUnderstand one-to-one, one-to-many, and many-to-many relationships and how they shape analytical queries.80 minarticle4 pages
Welcome and Learning Objectives
Introduce relationships between tables.
8 min
Types of Relationships
Explain common relationship patterns.
22 min
E-Commerce Relationship Model
Show a realistic relationship model.
25 min
Exercise - E-Commerce Relationship Model
Students model an e-commerce database.
25 min
Lesson 4: Primary Keys and Foreign KeysUnderstand primary keys, foreign keys, constraints, and how they protect data integrity.80 minarticle5 pages
Welcome and Learning Objectives
Introduce keys and integrity.
8 min
Primary Keys
Explain primary keys.
20 min
Foreign Keys and Constraints
Explain foreign keys and constraints.
22 min
Keys in Analytical Queries
Connect keys to SQL analysis.
18 min
Exercise - Key Integrity Diagram
Students create a key-based relationship diagram.
12 min
Lesson 5: Mini Project 1 - Database Blueprint ChallengeDesign a beginner-friendly relational database blueprint for a CRM, LMS, or e-commerce business.90 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
2Phase 2 - Querying DataLearn the SQL fundamentals required to retrieve, filter, sort, and calculate business data.1 modules5 lessons1–2 weeks
Module 1: SQL FundamentalsBuild core SQL query confidence using SELECT, WHERE, sorting, limiting, expressions, and CASE logic.5 lessons
Lesson 1: SELECT StatementsLearn how to select columns, create aliases, and build expressions.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided SQL exercise.
20 min
Lesson 2: Filtering DataUse WHERE, AND, OR, IN, BETWEEN, and LIKE to retrieve relevant business records.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
Lesson 3: Sorting and LimitingUse ORDER BY and LIMIT/TOP concepts to rank and inspect records.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided SQL exercise.
17 min
Lesson 4: Calculated FieldsCreate derived columns using arithmetic and CASE statements.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided SQL exercise.
20 min
Lesson 5: Mini Project 2 - Sales Insight Query PackWrite a practical set of SQL queries for sales, revenue, customer, and product analysis.80 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
3Phase 3 - Aggregation and ReportingUse SQL aggregation to build business KPI reporting datasets.1 modules5 lessons1–2 weeks
Module 1: Business Reporting with SQLUse COUNT, SUM, AVG, MIN, MAX, GROUP BY, HAVING, and KPI logic for reporting.5 lessons
Lesson 1: Aggregate FunctionsUse COUNT, SUM, AVG, MIN, and MAX to summarize business data.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided SQL exercise.
20 min
Lesson 2: GROUP BYGroup records by category, region, time, or customer segment.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
Lesson 3: HAVINGFilter aggregated results using HAVING.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided SQL exercise.
17 min
Lesson 4: Business KPI ReportingBuild SQL reports for revenue, customer growth, and retention metrics.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided SQL exercise.
25 min
Lesson 5: Milestone Project 1 - Executive KPI Reporting DatasetProduce dashboard-ready SQL datasets for executive KPI reporting.100 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
4Phase 4 - SQL Joins MasteryMaster the SQL joins needed to combine data across business tables accurately.1 modules6 lessons1–2 weeks
Module 1: Combining DataUse joins to connect customers, orders, products, payments, and other business tables.6 lessons
Lesson 1: INNER JOINUse INNER JOIN to return matching records across tables.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided SQL exercise.
20 min
Lesson 2: LEFT JOINUse LEFT JOIN to preserve records from the left table and analyze missing activity.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
Lesson 3: RIGHT JOIN and FULL JOINUnderstand completeness analysis using RIGHT JOIN and FULL JOIN concepts.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided SQL exercise.
17 min
Lesson 4: Multi-Table JoinsJoin several tables to build full business intelligence datasets.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided SQL exercise.
27 min
Lesson 5: Join Optimization ConceptsUnderstand efficient joins, common mistakes, and how poor joins create slow or wrong results.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided SQL exercise.
20 min
Lesson 6: Project - Customer Revenue AnalyticsBuild customer value, order, and revenue analysis using joins.90 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
5Phase 5 - Advanced SQL for AnalyticsUse subqueries, CTEs, window functions, trends, and retention analysis for advanced reporting.1 modules6 lessons2 weeks
Module 1: Analytical SQLDevelop advanced analytical SQL patterns for complex business questions.6 lessons
Lesson 1: SubqueriesUse nested and correlated queries for advanced reporting.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
Lesson 2: Common Table ExpressionsUse WITH statements to organize complex SQL logic.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided SQL exercise.
25 min
Lesson 3: Window FunctionsUse ROW_NUMBER, RANK, DENSE_RANK, LEAD, and LAG for analytical reporting.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided SQL exercise.
27 min
Lesson 4: Running Totals and TrendsUse SQL to calculate running totals, growth, and time-series reporting.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided SQL exercise.
25 min
Lesson 5: Cohort and Retention AnalysisBuild beginner-friendly cohort and retention analysis for subscription or repeat-use businesses.75 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
37 min
Practice Activity
Apply the lesson through a guided SQL exercise.
30 min
Lesson 6: Milestone Project 2 - Subscription Growth and Retention AnalyticsAnalyze subscription growth, retention, and cohorts with advanced SQL.110 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
6Phase 6 - Real-World Data AnalysisUse SQL to solve customer, product, marketing, and operations problems.1 modules4 lessons1–2 weeks
Module 1: Solving Business ProblemsApply SQL to practical business domains and reporting needs.4 lessons
Lesson 1: Customer AnalyticsUse SQL for customer segmentation, value analysis, and lifetime value concepts.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
Lesson 2: Product AnalyticsAnalyze product performance, product adoption, and revenue contribution.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
Lesson 3: Marketing AnalyticsAnalyze campaign performance and conversion metrics using SQL.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
Lesson 4: Operational AnalyticsBuild operational datasets for process, efficiency, and performance analysis.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
7Phase 7 - Professional SQLDevelop production-quality SQL habits for performance, maintainability, documentation, and BI collaboration.1 modules3 lessons1 week
Module 1: Production SQL SkillsWrite SQL that is readable, maintainable, dashboard-ready, and safer for production-scale work.3 lessons
Lesson 1: Query OptimizationLearn how to read queries, recognize performance basics, and understand index concepts.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided SQL exercise.
25 min
Lesson 2: Documentation and MaintainabilityWrite SQL that other analysts and engineers can understand and reuse.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided SQL exercise.
20 min
Lesson 3: Working with BI ToolsPrepare SQL datasets for Power BI, dashboards, and analytics platforms.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided SQL exercise.
22 min
8Phase 8 - Capstone, Graduation and PortfolioComplete an end-to-end SQL analytics capstone and package portfolio-ready SQL work.1 modules2 lessons1 week
Module 1: End-to-End Business Analytics CapstoneStudents complete an industry-based SQL analytics capstone and prepare their portfolio outcome.2 lessons
Lesson 1: Final Capstone - End-to-End Business Analytics ProjectBuild a professional SQL analytics project for one selected industry.150 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
Lesson 2: Graduation Requirements and Portfolio OutcomeClarify completion requirements and expected portfolio outputs.45 minarticle1 pages
Requirements and Portfolio Checklist
Summarize graduation requirements and portfolio assets.
45 min
5Beginner to Intermediate8 weeksPython for Data AnalyticsLearn Python for real analytics work: data cleaning, exploration, transformation, automation, and visual insight generation.8 phases12 modules54 lessons164 pages
1Phase 1 - Python Foundations for AnalystsBuild Python foundations for analytics: tool selection, environment setup, Jupyter workflow, syntax, control flow, data structures, reusable functions, and a metrics calculator project.2 modules9 lessons2 weeks
Module 1: Getting Started with Python for DataUnderstand why Python matters for analytics, set up the environment, use notebooks professionally, and learn essential syntax.4 lessons
Lesson 1: Why Python for Data AnalyticsUnderstand why analysts use Python, how it compares with Excel, SQL, and Power BI, and where it fits in a modern analytics workflow.85 minarticle6 pages
Welcome and Learning Objectives
Introduce Python's role in the analytics journey.
8 min
Why Analysts Use Python
Explain Python's practical value for analysts.
18 min
Excel vs SQL vs Power BI vs Python
Compare common analytics tools and when each fits best.
22 min
Where Python Fits in the Analytics Workflow
Show Python's place in end-to-end data analysis.
18 min
Real-World Data Use Cases
Connect Python analytics to real businesses.
18 min
Exercise - Analytics Tool Decision Matrix
Students identify when to use Excel, SQL, Power BI, or Python.
19 min
Lesson 2: Python Environment SetupSet up a working Python analytics environment using Python, Anaconda or Miniconda, Jupyter, VS Code, and package installation tools.90 minarticle5 pages
Welcome and Learning Objectives
Introduce the setup required for Python analytics.
8 min
The Tools You Need
Explain the setup tools in plain English.
20 min
Recommended Environment Structure
Show students how to organize their analytics environment.
18 min
Package Installation and Verification
Introduce package installation and verification commands.
22 min
Exercise - Analytics Environment Setup
Students set up a working Python analytics environment.
22 min
Lesson 3: Working in Jupyter NotebooksLearn how to use Jupyter notebooks for organized, reproducible, and stakeholder-readable data analysis.85 minarticle5 pages
Welcome and Learning Objectives
Introduce notebooks as the main analysis workspace.
8 min
Cells, Markdown and Code
Explain notebook building blocks.
18 min
Notebook Organization
Teach professional notebook structure.
20 min
Reproducible Analysis
Explain why rerunnable notebooks matter.
17 min
Exercise - First Analysis Notebook
Students create their first organized analysis notebook.
22 min
Lesson 4: Python Syntax EssentialsLearn the Python syntax essentials analysts need: variables, data types, operators, comments, and naming conventions.90 minarticle5 pages
Welcome and Learning Objectives
Introduce core syntax for analysis.
8 min
Variables and Data Types
Explain variables and data types through business examples.
20 min
Operators, Comments and Naming
Teach calculations and readability basics.
22 min
Business Calculation Examples
Connect syntax to common analytics metrics.
20 min
Exercise - Business Calculation Challenges
Students practice syntax with real business metrics.
20 min
Module 2: Python Control Flow and Data StructuresUse conditions, loops, Python data structures, and functions to represent business logic and reusable calculations.5 lessons
Lesson 1: ConditionsUse if, elif, else, comparison operators, and business rules in Python.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Python exercise.
20 min
Lesson 2: LoopsUse for loops and while loops while understanding when loops are unnecessary in data analysis.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Python exercise.
20 min
Lesson 3: Lists, Tuples, Sets and DictionariesRepresent customer and order data using Python collections.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 4: Functions for Reusable AnalysisCreate reusable functions for calculations and business metrics.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 5: Mini Project 1 - Business Metrics CalculatorBuild a Python notebook or script that calculates common business metrics using reusable functions.90 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
2Phase 2 - NumPy and Numerical AnalysisUse NumPy for numerical arrays, vectorized operations, descriptive statistics, outliers, distributions, and group comparisons.1 modules4 lessons1 week
Module 1: NumPy for AnalystsBuild numerical analysis foundations with arrays and vectorized operations.4 lessons
Lesson 1: Introduction to NumPyUnderstand arrays, why NumPy exists, lists vs arrays, and vectorized operations.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Python exercise.
20 min
Lesson 2: Array OperationsUse indexing, slicing, broadcasting, and mathematical operations on arrays.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 3: Descriptive Statistics with NumPyUse NumPy for mean, median, standard deviation, percentiles, min, and max.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 4: Practical Numerical AnalysisAnalyze outliers, distributions, summary statistics, and group comparisons.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
3Phase 3 - Pandas for Data AnalysisUse Pandas to load, inspect, select, filter, clean, transform, and prepare real datasets.2 modules10 lessons2 weeks
Module 1: Pandas FundamentalsLearn Series, DataFrames, data loading, inspection, selection, and filtering.4 lessons
Lesson 1: Introduction to PandasUnderstand Series, DataFrames, indexes, and why Pandas is central to analytics.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 2: Loading DataLoad data from CSV, Excel, JSON, SQL-style outputs, and file paths.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 3: Inspecting DataUse head, tail, info, describe, shape, columns, and dtypes for first-pass inspection.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 4: Selecting and Filtering DataSelect columns, filter rows, use boolean masks, loc, and iloc.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Module 2: Data Cleaning with PandasHandle missing data, duplicates, data type conversion, text cleaning, and date analysis.6 lessons
Lesson 1: Handling Missing DataDetect, drop, fill, and reason about missing data with business judgment.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 2: Removing DuplicatesRemove duplicate rows and duplicate keys while understanding business risks.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Python exercise.
20 min
Lesson 3: Data Type ConversionConvert numeric, date, categorical, and string data types.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 4: Text CleaningUse string methods to clean customer names, locations, and product categories.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 5: Date and Time AnalysisUse datetime, extract month/year/day, filter periods, and analyze monthly patterns.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 6: Mini Project 2 - Messy Dataset Cleaning ProjectClean a messy business dataset and produce a documented cleaning report.100 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
4Phase 4 - Data Transformation and Business AnalysisTransform data with Pandas and perform exploratory data analysis for business insights.2 modules11 lessons2 weeks
Module 1: Transforming Data with PandasUse sorting, ranking, grouping, pivot tables, merging, joins, and feature creation for business analysis.5 lessons
Lesson 1: Sorting and RankingFind top customers, bottom products, and ranked business outputs.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Python exercise.
20 min
Lesson 2: Grouping and AggregationUse groupby and aggregate for grouped KPIs.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 3: Pivot Tables in PandasBuild Excel-style summary tables in Python.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 4: Merging and Joining DataFramesCombine customers, orders, and products datasets correctly.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Python exercise.
27 min
Lesson 5: Feature Creation for AnalyticsCreate calculated columns, customer segments, revenue bands, flags, and derived metrics.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Module 2: Exploratory Data AnalysisAsk questions, form hypotheses, analyze distributions, relationships, trends, customers, and products.6 lessons
Lesson 1: What Is EDA?Understand exploratory data analysis, questions, hypotheses, patterns, and avoiding premature conclusions.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Python exercise.
20 min
Lesson 2: Univariate AnalysisAnalyze one variable at a time using distributions, frequencies, and summary statistics.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 3: Bivariate AnalysisAnalyze relationships between two variables using correlation and group comparisons.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 4: Time-Series ExplorationExplore trends, seasonality, rolling averages, and monthly/weekly analysis.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 5: Customer and Product AnalyticsAnalyze customer segmentation, product performance, repeat customers, and retention basics.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Python exercise.
27 min
Lesson 6: Milestone Project 1 - E-Commerce Exploratory AnalysisPerform a full EDA project on an e-commerce dataset.120 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
5Phase 5 - Data Visualization with PythonUse Matplotlib, Seaborn, Plotly, and storytelling principles to communicate insights visually.2 modules9 lessons1–2 weeks
Module 1: Visualization FundamentalsCreate clear static, statistical, and interactive visuals for business analysis.5 lessons
Lesson 1: Why Visualization MattersUnderstand charts as communication and choose visuals based on audience and question.50 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
25 min
Practice Activity
Apply the lesson through a guided Python exercise.
17 min
Lesson 2: Matplotlib BasicsCreate line charts, bar charts, histograms, scatter plots, and labeled visuals.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 3: Seaborn for Statistical VisualizationUse count plots, box plots, distribution plots, heatmaps, and category comparisons.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 4: Plotly for Interactive VisualizationCreate interactive charts, tooltips, dashboard-style visuals, and exported visuals.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 5: Visualization StorytellingUse titles, annotations, chart sequence, and insight-first visuals for executive reporting.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Module 2: Reporting with PythonTurn notebooks into professional reports, export outputs, and automate repetitive analysis.4 lessons
Lesson 1: Analytical Notebooks as ReportsStructure notebooks with executive summary, methodology, findings, and recommendations.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
Lesson 2: Exporting ResultsExport CSV, Excel, charts, and notebooks for stakeholders.55 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
27 min
Practice Activity
Apply the lesson through a guided Python exercise.
20 min
Lesson 3: Automating Repetitive AnalysisUse reusable scripts, scheduled reporting concepts, parameterized notebooks, and report templates.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Python exercise.
27 min
Lesson 4: Milestone Project 2 - Python Business Reporting ProjectBuild a reusable analysis report for a selected business domain.120 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
6Phase 6 - Working with Real Data SourcesLoad and analyze data from Excel files, JSON, APIs, SQL databases, and end-to-end analytics workflows.1 modules5 lessons1–2 weeks
Module 1: Data from Files, APIs and DatabasesWork with practical data sources used in real analytics teams.5 lessons
Lesson 1: Working with Excel FilesRead Excel sheets, multiple sheets, write Excel outputs, and format outputs.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 2: Working with JSON DataHandle nested JSON, normalize JSON, and work with API-style records.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 3: Working with APIsUse requests, API responses, status codes, pagination basics, and authentication concepts.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Python exercise.
27 min
Lesson 4: Connecting Python to SQL DatabasesConnect to databases, read SQL into Pandas, write query results, and combine SQL with Python workflows.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
35 min
Practice Activity
Apply the lesson through a guided Python exercise.
27 min
Lesson 5: End-to-End Data WorkflowBuild a mini pipeline that extracts, cleans, transforms, analyzes, visualizes, and reports data.80 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
40 min
Practice Activity
Apply the lesson through a guided Python exercise.
32 min
7Phase 7 - Professional Analytics WorkflowBuild professional habits for notebooks, project organization, Git, communication, and stakeholder-ready findings.1 modules4 lessons1 week
Module 1: Code Quality for AnalystsImprove readability, reproducibility, organization, version control, and communication.4 lessons
Lesson 1: Clean Notebook PracticesMake notebooks readable, remove dead code, add comments, improve reproducibility, and clean outputs.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 2: Project OrganizationStructure data projects with folders, raw/processed data, notebooks, reports, src, and README.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 3: Version Control for Data ProjectsUse Git basics for notebooks, committing analysis work, README documentation, and portfolio repositories.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
30 min
Practice Activity
Apply the lesson through a guided Python exercise.
22 min
Lesson 4: Communicating FindingsWrite stakeholder communication, executive summaries, recommendations, limitations, and next steps.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Business Examples
Explain the concept with practical business examples.
32 min
Practice Activity
Apply the lesson through a guided Python exercise.
25 min
8Phase 8 - Capstone, Graduation and PortfolioComplete an end-to-end Python analytics capstone and package a portfolio-ready repository.1 modules2 lessons1 week
Module 1: End-to-End Python Data Analytics CapstoneStudents complete an industry-based capstone project using Python, Pandas, visualization, reporting, and professional project organization.2 lessons
Lesson 1: Final Capstone - End-to-End Python Data Analytics ProjectBuild a professional Python analytics project for one selected industry.160 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
Lesson 2: Graduation Requirements and Portfolio OutcomeClarify completion requirements and expected portfolio outputs.45 minarticle1 pages
Requirements and Portfolio Checklist
Summarize graduation requirements and portfolio assets.
45 min
6Intermediate6 weeksPath onlyData Analytics StudioApply Excel, SQL, Python, Power BI, and storytelling to complete end-to-end analytics projects for your portfolio.8 phases9 modules42 lessons124 pages
1Phase 1 - From Business Problem to Analytics PlanTeach students how to translate vague business requests into a scoped analytics brief with stakeholders, questions, KPIs, risks, assumptions, and deliverables.1 modules5 lessons1 week
Module 1: Analytics Project DiscoveryUnderstand business context, gather stakeholder requirements, define KPIs, plan analytics projects, and produce an analytics brief.5 lessons
Lesson 1: Understanding the Business ContextLearn how to understand the business problem before touching data, tools, charts, SQL, Python, or dashboards.85 minarticle6 pages
Welcome and Learning Objectives
Introduce business-context-first analytics.
8 min
The Business Problem Comes First
Explain the importance of problem understanding.
18 min
Stakeholders, Decisions and Success
Clarify the core project context.
20 min
Avoiding Analysis Without Business Purpose
Teach students how to avoid random analysis.
18 min
Scenario Walkthrough
Show how to decode a vague stakeholder request.
18 min
Exercise - Find the Real Decision
Students identify the real business decision behind a scenario.
21 min
Lesson 2: Stakeholder RequirementsLearn how to ask good stakeholder questions, clarify vague requests, separate nice-to-have items from decision-critical needs, and write analytics requirements.85 minarticle5 pages
Welcome and Learning Objectives
Introduce stakeholder requirements.
8 min
How to Ask Better Questions
Teach stakeholder questioning.
20 min
Decision-Critical vs Nice-to-Have
Teach prioritization.
18 min
Writing Analytics Requirements
Show a requirements structure.
20 min
Exercise - Convert a Vague Dashboard Request
Students convert a vague dashboard request into clear requirements.
19 min
Lesson 3: Defining Metrics and KPIsLearn how to define metrics, KPIs, leading and lagging indicators, vanity metrics, ownership, and calculation definitions.85 minarticle5 pages
Welcome and Learning Objectives
Introduce KPI definition for studio projects.
8 min
Metrics vs KPIs
Explain metric categories.
18 min
Leading, Lagging and Vanity Metrics
Teach metric judgment.
18 min
KPI Definition Template
Give a reusable KPI definition structure.
20 min
Exercise - KPI Definition Studio
Students create KPI definitions for a selected business.
21 min
Lesson 4: Analytics Project PlanningLearn how to plan analytics project scope, deliverables, timeline, data sources, risks, and assumptions.85 minarticle5 pages
Welcome and Learning Objectives
Introduce analytics project planning.
8 min
Scope and Deliverables
Teach scope control.
20 min
Timeline, Data Sources, Risks and Assumptions
Explain planning details.
22 min
One-Page Analytics Project Plan
Provide a reusable project plan structure.
18 min
Exercise - One-Page Analytics Project Plan
Students write a project plan.
17 min
Lesson 5: Mini Project 1 - Analytics BriefStudents choose one business case and produce a professional analytics brief that anchors the studio project.100 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
2Phase 2 - Data Audit, Cleaning and PreparationAudit available data, document quality issues, choose cleaning strategies, and prepare analysis-ready datasets.1 modules5 lessons1 week
Module 1: Data UnderstandingReview data sources, audit data quality, plan cleaning work, and design a reproducible preparation workflow.5 lessons
Lesson 1: Data Source ReviewReview available datasets, required tables/files, data dictionaries, source reliability, and ownership.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
30 min
Practice Activity
Apply the lesson through a guided studio activity.
22 min
Lesson 2: Data Quality AuditAudit missing values, duplicates, invalid categories, date issues, outliers, inconsistent IDs, and broken relationships.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 3: Cleaning StrategyChoose what to clean in Excel, SQL, Python, or Power Query and document cleaning decisions.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
30 min
Practice Activity
Apply the lesson through a guided studio activity.
22 min
Lesson 4: Data Preparation WorkflowDesign raw, cleaned, analysis-ready, dashboard-ready, and reproducible data workflows.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
32 min
Practice Activity
Apply the lesson through a guided studio activity.
25 min
Lesson 5: Mini Project 2 - Data Quality and Preparation ReportProduce a data dictionary, data quality audit, cleaning plan, risk notes, and prepared analysis dataset.90 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
3Phase 3 - SQL Analytics LayerUse SQL to translate business questions into queries and create dashboard-ready reporting outputs.1 modules5 lessons1 week
Module 1: Building Reporting Datasets with SQLBuild KPI, segmentation, trend, and dashboard-ready SQL outputs.5 lessons
Lesson 1: Translating Questions into SQLTurn business questions into SQL plans before writing queries.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
30 min
Practice Activity
Apply the lesson through a guided studio activity.
22 min
Lesson 2: KPI QueriesWrite SQL queries for revenue, orders, customers, conversion, retention, churn, and growth.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 3: Segmentation QueriesCreate customer, product, geographic, cohort, and campaign segment reports.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
32 min
Practice Activity
Apply the lesson through a guided studio activity.
25 min
Lesson 4: Dashboard-Ready SQL OutputsCreate clean reporting tables, naming conventions, reusable views, and documented query outputs.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 5: Milestone Project 1 - SQL Reporting LayerProduce the SQL reporting layer for the studio project.110 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
4Phase 4 - Python Exploratory AnalysisUse Python to explore patterns, trends, customer/revenue behavior, operational issues, and insight statements.1 modules6 lessons1–2 weeks
Module 1: Exploratory Data Analysis with PythonUse Python notebooks for deeper analysis and evidence-based insight generation.6 lessons
Lesson 1: EDA StrategyExplore data systematically using questions, hypotheses, patterns, and group comparisons.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
30 min
Practice Activity
Apply the lesson through a guided studio activity.
22 min
Lesson 2: Customer and Revenue AnalysisAnalyze customer value, repeat customers, revenue distribution, segment behavior, and retention indicators.75 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
37 min
Practice Activity
Apply the lesson through a guided studio activity.
30 min
Lesson 3: Product, Campaign or Operations AnalysisAnalyze product performance, campaign performance, process bottlenecks, operational efficiency, and outliers.75 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
37 min
Practice Activity
Apply the lesson through a guided studio activity.
30 min
Lesson 4: Trend and Time-Based AnalysisAnalyze monthly/weekly trends, seasonality, growth rates, and rolling averages.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 5: From Analysis to InsightTurn evidence into interpretation, limitations, business implication, and recommendation.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
32 min
Practice Activity
Apply the lesson through a guided studio activity.
25 min
Lesson 6: Milestone Project 2 - Python Insight NotebookProduce a clean Python insight notebook for the studio project.120 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
5Phase 5 - Power BI Decision DashboardPlan, build, refine, and validate a decision-focused Power BI dashboard.2 modules9 lessons1–2 weeks
Module 1: Dashboard Planning and DesignPlan dashboard purpose, wireframes, data model, measures, pages, and build sprint outputs.4 lessons
Lesson 1: Dashboard PurposeDecide executive, diagnostic, and operational dashboard pages based on audience and decisions.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
30 min
Practice Activity
Apply the lesson through a guided studio activity.
22 min
Lesson 2: Dashboard WireframingPlan layout, KPI placement, navigation, visual hierarchy, and filtering strategy.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
32 min
Practice Activity
Apply the lesson through a guided studio activity.
25 min
Lesson 3: Data Model ReviewReview fact/dimension thinking, relationships, date table, measure planning, and model documentation.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 4: Dashboard Build SprintBuild report pages, DAX measures, filters, tooltips, drill-through, and formatting consistency.90 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
45 min
Practice Activity
Apply the lesson through a guided studio activity.
37 min
Module 2: Insight-Driven BIBuild executive, diagnostic, and operational dashboard pages and run dashboard QA.5 lessons
Lesson 1: Executive Summary PageBuild an executive page with KPI cards, trends, alerts, narrative, and recommended actions.75 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
37 min
Practice Activity
Apply the lesson through a guided studio activity.
30 min
Lesson 2: Diagnostic Analysis PagesBuild drill-down views, segmentation, root-cause investigation, and comparative analysis pages.75 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
37 min
Practice Activity
Apply the lesson through a guided studio activity.
30 min
Lesson 3: Operational Monitoring PageBuild monitoring workflows, exceptions, SLA tracking, and team/region performance pages.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 4: Dashboard Review and RefinementRemove clutter, improve readability, test interactions, validate numbers, and run stakeholder review.65 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
32 min
Practice Activity
Apply the lesson through a guided studio activity.
25 min
Lesson 5: Milestone Project 3 - Power BI Decision DashboardProduce a decision-focused Power BI dashboard for the studio project.130 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
6Phase 6 - Communication, Presentation and Stakeholder DeliveryWrite executive insights, present findings, and prepare handover documentation.1 modules5 lessons1 week
Module 1: Data Storytelling for Business DecisionsTurn analysis into business communication and stakeholder-ready delivery.5 lessons
Lesson 1: Writing Insight StatementsDifferentiate observation, insight, recommendation, and evidence-based writing.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
30 min
Practice Activity
Apply the lesson through a guided studio activity.
22 min
Lesson 2: Executive ReportingWrite one-page summaries with key findings, risks, opportunities, recommended actions, assumptions, and limitations.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 3: Presenting to StakeholdersPresent methodology simply, handle questions, defend assumptions, and avoid tool-heavy presentations.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 4: Analytics HandoverCreate documentation, refresh instructions, data definitions, known limitations, and maintenance plan.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
30 min
Practice Activity
Apply the lesson through a guided studio activity.
22 min
Lesson 5: Mini Project 3 - Executive Insight PackPackage executive summary, findings, recommendations, dashboard walkthrough notes, and handover documentation.90 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
7Phase 7 - Portfolio, Interview and Career ReadinessPackage the analytics project into a credible portfolio case study and prepare for analytics interviews.1 modules4 lessons1 week
Module 1: Building an Analytics PortfolioBuild portfolio standards, case studies, GitHub packaging, and interview readiness.4 lessons
Lesson 1: Portfolio Project StandardsUnderstand credible portfolio projects, avoiding toy projects, case study structure, and showing business impact.60 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
30 min
Practice Activity
Apply the lesson through a guided studio activity.
22 min
Lesson 2: Writing Case StudiesWrite case studies with problem, data, method, insights, recommendations, tools, screenshots, and limitations.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 3: GitHub and Project PackagingPackage repositories with README, data privacy, notebook cleanup, dashboard screenshots, SQL folder, and Power BI notes.70 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
35 min
Practice Activity
Apply the lesson through a guided studio activity.
27 min
Lesson 4: Analytics Interview PreparationPrepare to explain projects, answer SQL questions, critique dashboards, discuss business cases, and explain cleaning decisions.75 minarticle3 pages
Overview and Learning Objectives
Introduce the lesson and clarify expected outcomes.
8 min
Concepts and Professional Workflow
Explain the concept through a professional analytics workflow.
37 min
Practice Activity
Apply the lesson through a guided studio activity.
30 min
8Phase 8 - Final Capstone and GraduationComplete the end-to-end business analytics capstone and package all final portfolio assets.1 modules3 lessons1 week
Module 1: End-to-End Business Analytics CapstoneStudents act as the data analyst for a business team and deliver a complete analytics project.3 lessons
Lesson 1: Studio Project OptionsChoose a realistic analytics project option for the final capstone.60 minarticle1 pages
Choose Your Capstone Scenario
Review approved studio project options.
60 min
Lesson 2: Final Capstone - End-to-End Business Analytics CapstoneStudents define a business problem, prepare data, analyze it with SQL and Python, build a Power BI dashboard, present insights, and package the project professionally.180 minarticle2 pages
Project Brief
Explain the project scenario and expected output.
20 min
Review Checklist
Checklist for project quality.
20 min
Lesson 3: Graduation Requirements and Portfolio OutcomeClarify completion requirements and portfolio outputs.55 minarticle1 pages
Graduation Requirements
Summarize what students must complete before graduation.
55 min
Skills and tools
Tools are taught through projects, not isolated checklists.
Clean, structure, and analyze business data.Use Excel for spreadsheet analysis and reporting.Write SQL queries to retrieve, join, filter, and summarize data.Use Python for data cleaning, exploration, and automation.Build interactive Power BI dashboards and business reports.Turn raw data into clear insights and recommendations.Communicate findings with charts, dashboards, reports, and presentations.Build portfolio-ready analytics projects.Prepare for junior data analyst and BI analyst roles.
Projects and portfolio
Clean, structure, and analyze business data.
Clean, structure, and analyze business data.
Use Excel for spreadsheet analysis and reporting.
Use Excel for spreadsheet analysis and reporting.
Write SQL queries to retrieve, join, filter, and summarize data.
Write SQL queries to retrieve, join, filter, and summarize data.
Use Python for data cleaning, exploration, and automation.
Use Python for data cleaning, exploration, and automation.
Build interactive Power BI dashboards and business reports.
Build interactive Power BI dashboards and business reports.
Turn raw data into clear insights and recommendations.
Turn raw data into clear insights and recommendations.
Communicate findings with charts, dashboards, reports, and presentations.
Communicate findings with charts, dashboards, reports, and presentations.
Build portfolio-ready analytics projects.
Build portfolio-ready analytics projects.
Prepare for junior data analyst and BI analyst roles.
Prepare for junior data analyst and BI analyst roles.
Portfolio outcomes
Clean, structure, and analyze business data.Use Excel for spreadsheet analysis and reporting.Write SQL queries to retrieve, join, filter, and summarize data.Use Python for data cleaning, exploration, and automation.Build interactive Power BI dashboards and business reports.Turn raw data into clear insights and recommendations.Communicate findings with charts, dashboards, reports, and presentations.Build portfolio-ready analytics projects.Prepare for junior data analyst and BI analyst roles.
Mentorship
Self-paced learning with feedback options.
TechOga paths are structured for independent progress, with stronger feedback loops available through weekly live-session and premium one-on-one support.
Structured course access for learners who can move independently and want clear lessons, resources, exercises, and portfolio direction.
A stronger support model with weekly instructor-led live sessions, weekly exercises, instructor reviews, and accountability across a path.
Self-paced access plus premium one-on-one sessions/mentorship for learners who want deeper review, private guidance, career assets, and tailored accountability.
Self-Paced Only
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Pay once or split into fixed installments.
Upfront Payment
₦250,000due today
- ₦250,000 at enrollment
Two-Part Installment
₦150,000due today
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- ₦100,000 after 30 days
Three-Part Installment
₦100,000due today
- ₦100,000 at enrollment
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Access starts after your first confirmed payment.
Self-Paced + Weekly Instructor-Led Live Sessions
₦350,000
Pay once or split into fixed installments.
Upfront Payment
₦350,000due today
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Two-Part Installment
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Three-Part Installment
₦140,000due today
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- ₦105,000 after 60 days
Access starts after your first confirmed payment.
Self-Paced + Premium One-on-One Sessions/Mentorship
₦549,000
Pay once or split into fixed installments.
Upfront Payment
₦549,000due today
- ₦549,000 at enrollment
Two-Part Installment
₦329,400due today
- ₦329,400 at enrollment
- ₦219,600 after 30 days
Three-Part Installment
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- ₦219,600 at enrollment
- ₦164,700 after 30 days
- ₦164,700 after 60 days
Access starts after your first confirmed payment.
FAQ
Questions about this path.
Path-specific answers keep the enrolment decision practical.
Yes. It starts with Data Foundations before moving into Excel, SQL, Python, Power BI, and analytics projects.
Start with structure
Become the kind of data analyst businesses can trust.
Build practical analytics skills, complete portfolio-ready projects, and learn how to communicate insights clearly for business, reporting, and decision-making roles.