3000+
learners trained
Across practical data, software, and career-readiness programmes.
Structured learning. Real portfolio proof.
Build tech skills you can prove.
Structured training for serious career moves.
Learn career-ready tech skills through structured lessons, instructor review, disciplined project work, and a portfolio that shows what you can actually do.
Mentor-reviewed project work
Structured paths for real career moves
Portfolio evidence over empty certificates
Built in Africa, benchmarked globally
300+
cohorts delivered
Structured learning experiences with exercises, feedback, and projects.
10+
industry projects
Real-world portfolio projects designed to prove practical skill.
100%
project-based paths
Every pathway is designed around evidence of real skill.
Admissions guidance
Get the right path recommendation before you commit.
The first step is not payment. It is clarity. Share your background, target role, weekly availability, and support needs, then admissions will point you to the best-fit route.
Clear path selection
Admissions helps you choose the route that fits your current level and goal.
Serious weekly rhythm
Lessons, exercises, project checkpoints, and reviews keep the work moving.
Work you can defend
Graduate with dashboards, notebooks, APIs, and capstones you can explain clearly.
Scholarships and sponsored training
Funded seats for learners. Cohort outcomes for sponsors.
TechOga scholarships connect serious learners to fully funded seats, partial scholarships, sponsored cohorts, and institutional digital skills programs funded by companies, NGOs, foundations, government programs, and TechOga initiatives.
Fully funded seats
Sponsor-backed seats can cover tuition for learners admitted into selected TechOga programs.
Partial scholarships
Funders can reduce learner cost while the remaining balance still moves through normal checkout.
Sponsored cohorts
Companies, NGOs, foundations, and public programs can fund cohort-based practical training.
Explore by school
Start with the career lane that fits you.
Skip the random course hunt. Choose Data, AI, or Software Engineering first, then follow the paths, projects, and focused courses built for that role.
School
School of Data & AI
Learn to turn data into insight, build intelligent systems, and create proof of skill through real projects.
Explore this schoolSchool
School of Engineering
Build real software systems, ship production-ready applications, and grow into a serious engineering professional.
Explore this schoolLearning paths
Choose the route. Build the evidence. Raise your standard.
Each path is designed as a serious progression, not a playlist of random lessons. You learn the foundations, practise deliberately, get the right level of support, and leave with work that shows how you think.
Complete route
Project sequence
Portfolio proof
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
Portfolio proof
Clean, structure, and analyze business data.
Course sequence preview
- 1
Data 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.
- 2
Excel for Data Analytics
Master the Excel skills used by data analysts to clean, organize, calculate, summarize, visualize, and report business data with confidence.
- 3
Power BI for Business Intelligence
Learn to connect, clean, model, measure, visualize, and present business data using Power BI.
- 4
SQL for Data Analytics
Learn the SQL skills data analysts use to extract, filter, join, group, and analyze data from relational databases.
- 5
Python for Data Analytics
Learn Python for real analytics work: data cleaning, exploration, transformation, automation, and visual insight generation.
- 6
Data Analytics Studio
Apply Excel, SQL, Python, Power BI, and storytelling to complete end-to-end analytics projects for your portfolio.
School of Data & AIBeginner to Intermediate8 courses
Data Engineering
Learn how to build the pipelines, data models, warehouses, orchestration workflows, and cloud data systems that power analytics, reporting, machine learning, and AI products.
Target role
Data Engineer
Duration
Flexible duration - Flexible weekly pace
Support
Choose your learning support level
Portfolio proof
Use Python to automate data movement and processing.
Course sequence preview
- 1
Data 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.
- 2
Python for Data Engineering
Learn the Python skills data engineers use to move, clean, transform, validate, and automate data across files, APIs, databases, and pipeline workflows.
- 3
SQL for Data Analytics
Learn the SQL skills data analysts use to extract, filter, join, group, and analyze data from relational databases.
- 4
Data Warehousing
Learn how modern teams organize trusted business data for analytics, reporting, and decision-making.
- 5
ETL & ELT Pipelines
Learn how to move data from source systems into databases, warehouses, and analytics layers using practical ETL and ELT pipeline workflows.
- 6
Orchestration with Airflow & dbt
Learn how to manage reliable data workflows using Airflow for orchestration and dbt for structured, tested, analytics-ready transformations.
+2 more courses complete the path.
School of Data & AIBeginner to Intermediate5 courses
Data Science & Machine Learning
Build practical data science and machine learning skills by learning Python, statistics, data preparation, model training, evaluation, interpretation, and end-to-end data science projects.
Target role
Data Scientist, Applied ML Engineer, Analytics Scientist
Duration
Flexible duration - Flexible weekly pace
Support
Choose your learning support level
Portfolio proof
Use Python for data cleaning, exploration, and analysis.
Course sequence preview
- 1
Data 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.
- 2
Python for Data Analytics
Learn Python for real analytics work: data cleaning, exploration, transformation, automation, and visual insight generation.
- 3
Statistics for Data Science
Build the statistical foundation needed to understand data, measure uncertainty, test assumptions, interpret patterns, and prepare for machine learning.
- 4
Applied Machine Learning
Apply machine learning to realistic datasets through feature engineering, model selection, evaluation, tuning, interpretation, and project presentation.
- 5
Data Science Studio
Complete end-to-end data science projects that combine problem framing, data cleaning, exploration, statistics, visualization, modeling, evaluation, storytelling, and presentation.
School of EngineeringBeginner to Intermediate4 courses
Full Stack Software Engineering
Learn how to build complete web applications with backend APIs, databases, authentication, frontend interfaces, deployment, and full-stack product delivery.
Target role
Full Stack Software Engineer, Web Developer, Frontend Software Engineer, Backend Software Engineer
Duration
Flexible duration - Flexible weekly pace
Support
Choose your learning support level
Portfolio proof
Understand how modern software applications work.
Course sequence preview
- 1
Software Engineering Foundations
Build the foundation for becoming a software engineer by learning how software works, how developers think, and how modern applications are planned, built, tested, and improved.
- 2
Backend Software Engineering with Python & Django
Learn how to build the server-side systems behind modern web, mobile, and desktop applications, including APIs, databases, authentication, permissions, testing, deployment, and production workflows.
- 3
Frontend Software Engineering with React, Next.js & TypeScript
Learn how to build beautiful, responsive, interactive web applications using React, Next.js, TypeScript, APIs, forms, authentication flows, and production-ready frontend workflows.
- 4
Full Stack Engineering Studio
Bring backend and frontend skills together to build complete, portfolio-ready web applications from idea to deployment.
How TechOga works
A serious rhythm from first lesson to portfolio review.
The model is deliberately simple: pick a route, build weekly momentum, submit real work, and use feedback to raise the quality.
Step 1
Choose a learning path
Start with a structured path mapped to a real career outcome.
Step 2
Learn at your pace
Follow lessons and resources around a realistic weekly commitment.
Step 3
Complete weekly exercises
Use guided practice to convert concepts into visible skill.
Step 4
Get instructor feedback
Submit selected work for review when you are on a weekly live-session or premium support tier.
Step 5
Book mentor check-ins
Use check-ins to clarify blockers, direction, and project quality.
Step 6
Build portfolio projects
Graduate with projects you can explain, refine, and share.
Mentorship and review
For learners who want feedback, direction, and higher standards.
Learners on weekly live-session or premium support get more than videos. They submit work, receive practical reviews, book check-ins where included, and refine projects until the decisions behind the work are visible.
Weekly exercises with clear rubrics
Instructor reviews on selected submissions
Project feedback focused on real-world quality
Mentor check-ins for momentum and direction
Portfolio guidance before public sharing
Career-focused reflection after major projects
Portfolio proof
Leave with projects that show more than output.
The strongest portfolios explain decisions. Learners build dashboards, notebooks, APIs, capstones, and writeups that make their thinking visible.
Business/Data AnalystBI AnalystJunior Data ScientistBackend DeveloperAnalytics EngineerTechnical Product/Data roles
Executive dashboards
Power BI dashboards built around real business questions and clear stakeholder decisions.
SQL case studies
Analytical SQL projects with assumptions, queries, findings, and recommendation notes.
Python notebooks
Exploratory analysis notebooks with clean code, visuals, and written insight.
Machine learning projects
Modeling projects that document framing, evaluation, limitations, and next steps.
Backend APIs
Django APIs with authentication, validation, tests, and practical resource workflows.
Capstone writeups
Portfolio-ready case studies that explain the problem, process, decisions, and result.
Support tiers
Choose the level of guidance that matches your ambition.
Each course and learning path has its own tuition by support level, with upfront, 2-part, and 3-part fixed payment options.
Self-Paced Only
Varies by course/path
Pay upfront or split this selected course/path into fixed installments
Structured course access for learners who can move independently and want clear lessons, resources, exercises, and portfolio direction.
- Best for
- Disciplined learners building foundations alongside work or school.
- Mentorship
- Resource-led support
- Access
- Flexible access window
- Course access
- Downloadable resources
- Exercises and project briefs
- Portfolio guidance templates
Self-Paced + Weekly Instructor-Led Live Sessions
Most guidedVaries by course/path
Pay upfront or split weekly live-session support into fixed installments
A stronger support model with weekly instructor-led live sessions, weekly exercises, instructor reviews, and accountability across a path.
- Best for
- Learners who want live instructor guidance, structure, and momentum.
- Mentorship
- Weekly instructor-led live sessions
- Access
- Structured access window
- Everything in Self-Paced
- Weekly instructor-led live sessions
- Weekly exercise structure
- Instructor reviews
- Portfolio feedback
Self-Paced + Premium One-on-One Sessions/Mentorship
Varies by course/path
Pay upfront or split premium one-on-one support into fixed installments
Self-paced access plus premium one-on-one sessions/mentorship for learners who want deeper review, private guidance, career assets, and tailored accountability.
- Best for
- Career switchers and professionals who need focused guidance.
- Mentorship
- Premium one-on-one sessions and roadmap support
- Access
- Custom access window
- Everything in weekly live sessions
- Priority reviews
- One-on-one sessions/mentorship
- Portfolio review
- CV/LinkedIn/GitHub review
- Mock interview support
Learner voice
Real progress sounds specific.
The stories are not inflated promises. They are about structure, feedback, confidence, and project work that became easier to explain.
Project work reviewed by humans, not auto-marked into silence.
“The structure helped me stop jumping between random tutorials. I knew what to study each week, what to submit, and how to improve the project.”
Amina Yusuf
Data Analytics learner
SQL and BI
“The feedback was direct and practical. My notebook moved from a class exercise to something I could actually explain in a portfolio review.”
Daniel Okafor
Applied Data Science learner
Python and ML
“I liked that the backend path focused on real API decisions, not just syntax. The project reviews made me think like an engineer.”
Mariam Bello
Backend Engineering learner
Python and Django
FAQ
Questions people ask before choosing a path.
Clear answers on structure, support, projects, and how admissions helps you choose the right route.
Yes. You can register interest whenever you are ready. Some courses start immediately after enrollment, while cohort-based courses or paths start on scheduled dates. Your confirmed start date appears in your Learn dashboard after enrollment.
Admissions guidance
Get clear guidance before you commit.
Tell admissions where you are starting from, what you want to build, and how much guidance you need. We will help you choose the path and support level that makes sense.