Four phases. One outcome.
Every student moves through the same journey — foundation, specialisation, a real team-built product, and a focused career launch. One fee covers all four.
Foundation
Digital & Business Foundations — digital fluency, structured problem-solving, business thinking, and AI literacy. Everyone in the cohort completes Phase 1.
Specialisation
Go deep in one of eight tracks (or an advanced track) with a structured, week-by-week, project-based curriculum. You advance after scoring 60% cumulatively in Phase 1.
Real Project Labs
Join a cross-functional team and build a real, live product — discovery, architecture, two build sprints, user testing, and polish — ending in a public Demo Day open to employers and the community.
Career Launch
Choose your path — employment, freelancing, or startup — and execute it. You leave with a portfolio, a professional presence, a 90-day plan, and a real career action already taken.
Advancing to Phase 2 requires a cumulative score of at least 60% in Phase 1 — attendance, assignments, participation, and the capstone project all count.
One fee covers your full programme, end to end — Phase 1, your Phase 2 specialisation, and the Project Labs and Career Launch stages that follow.
Our Teaching Philosophy
“What is the judgment call AI cannot make here — and how do you make it well?”
Foundations
Tools, syntax, frameworks — the technical base you need to operate.
Judgment
Catch AI errors, make defensible decisions, know when to trust and when to question.
Communication
Explain what you built, why you built it, and what you would do differently.
AI is not the enemy of this programme — it is the test.
AI Challenge (Weekly)
Do your work first. Then bring AI in for a specific comparison. Document what changed. AI comes second — always.
AI Audit (Every 2–3 weeks)
Given an AI output, find what it got wrong and why. Group exercise.
AI Assistant (Always On)
Socratic-style assistant that asks questions, never gives answers.
Every track, week by week
Phase 1: Digital & Business Foundations
● Enrolling nowThe mandatory foundation every E-Technix student completes before specialising. You will leave with digital fluency, business thinking, and AI literacy that every employer and client now expects — regardless of which track you go into.
- →Understand how digital products, platforms, and businesses work
- →Solve structured problems using frameworks professionals use daily
- →Navigate and critically evaluate AI tools rather than blindly depend on them
- →Communicate your ideas clearly in written and presentation formats
- →Build a personal digital presence ready for your specialisation track
Data Analytics
● Enrolling nowTurn raw data into decisions. You will learn to collect, clean, analyse, and visualise data — then communicate what it means to people who did not see the numbers. This track is built for the Nigerian business context, using real local datasets and tools that actual companies hire for.
- →Query databases using SQL to extract and transform data
- →Clean and analyse data using Python (pandas) or Excel
- →Build dashboards and visualisations using Power BI or Google Looker Studio
- →Write data stories that non-technical stakeholders can act on
- →Complete an end-to-end data project from raw CSV to boardroom recommendation
Web App Development
● Enrolling nowBuild web applications that work — and that you can explain, defend, and maintain. This track takes you from HTML fundamentals to deploying a full-stack Next.js application with a real database. Every week, AI will be your tool, not your crutch.
- →Build responsive, accessible web interfaces using HTML, CSS, and JavaScript
- →Develop full-stack web applications with React and Next.js
- →Connect applications to real databases using Supabase/PostgreSQL
- →Deploy and maintain web applications on Vercel or similar platforms
- →Review and debug AI-generated code with confidence
Mobile & Desktop Apps
● Enrolling nowBuild apps that run everywhere — Android, iOS, and Windows — from a single codebase using Flutter. This is one of the most in-demand skills in the Nigerian market, where mobile-first is not a trend but a reality.
- →Build cross-platform mobile and desktop applications using Flutter and Dart
- →Design clean, responsive UI layouts using Flutter’s widget system
- →Connect apps to real backends using Supabase or Firebase
- →Publish a working app to Google Play or as a Windows executable
- →Read, debug, and improve AI-generated Flutter code
AI & Agentic Systems
● Enrolling nowBuild AI-powered products — not just use them. You will learn how modern AI systems work, how to integrate them into applications, how to build agents that take actions autonomously, and — critically — how to know when they are wrong. This is not a prompt engineering course. This is engineering with AI.
- →Understand how large language models work without needing a PhD
- →Integrate AI APIs (OpenAI, Anthropic, Groq) into real applications
- →Build agentic systems that plan, use tools, and take actions
- →Evaluate AI output quality and build guardrails for production systems
- →Design and ship an AI-powered product from idea to deployment
Product Design
● Enrolling nowDesign digital products that people actually want to use. This track covers the full product design process — from user research and wireframing to high-fidelity prototypes and design systems — using Figma as your primary tool. Design in the Nigerian context: understand the users, the devices, the bandwidth constraints, and the cultural expectations that global design tutorials ignore.
- →Run user research and translate findings into design decisions
- →Build wireframes, user flows, and interactive prototypes in Figma
- →Design accessible, responsive interfaces for mobile and web
- →Create and maintain a design system
- →Present and defend design decisions to developers and stakeholders
Digital Entrepreneurship
● Enrolling nowBuild a real digital business — not a pitch deck. This track covers customer acquisition, revenue generation, digital marketing, sales, and the operational realities of running a Nigerian digital business. By the end, you will have a working business plan, a tested acquisition strategy, and your first or next customer.
- →Validate a business idea with real customer conversations before building anything
- →Build and execute a digital marketing strategy across the right channels for Nigeria
- →Generate revenue: structure pricing, close sales, and retain customers
- →Build operational systems that do not require you to be present for every decision
- →Present a fundable business case to investors or grant committees
AI Product Management
● Enrolling nowProduct managers decide what gets built, why, and for whom. AI Product Managers do all of that — and also understand what AI can and cannot do well enough to make those decisions without being misled by engineers or vendors. This track is for people who want to lead product teams, not just join them.
- →Write product requirements that engineers can actually build from
- →Prioritise ruthlessly using data, user research, and strategy
- →Understand AI capabilities and limitations well enough to make sound product decisions
- →Run an effective product development cycle from discovery to launch
- →Build a product portfolio demonstrating PM thinking, not just execution
Cybersecurity Fundamentals
● Enrolling nowCybersecurity is one of the fastest-growing fields in Nigeria and globally. This track gives you a rigorous foundation — how attacks happen, how defences work, and how to think like both an attacker and a defender. By the end, you will have hands-on lab experience and a portfolio of security assessments that demonstrates real skill, not just certificates.
- →Understand how common cyberattacks work at a technical level
- →Identify vulnerabilities in networks, applications, and human behaviour
- →Apply defensive security practices in real environments
- →Use professional security tools including Kali Linux, Wireshark, and Burp Suite
- →Communicate security risks clearly to both technical and non-technical audiences
Data Engineering
▲ Advanced● Enrolling nowData analysts answer questions. Data engineers build the systems that make answering questions possible at scale. This advanced track covers data pipeline architecture, warehousing, transformation, and infrastructure — the foundational layer that every data team depends on.
- →A faster pace and a heavier workload than a standard specialisation (12–15 hours/week).
- →Strong SQL and Python assumed from day one — you build pipelines, not spreadsheets.
- →Entry is by application: either complete Data Analytics, or pass a placement assessment that proves equivalent experience.
Advanced tracks are open for enrolment now, but you must complete the prerequisite track first. If you already have the experience, you can sit a placement assessment to verify it and enter the advanced track directly — no one skips the prerequisite on an unverified claim.
- →Design and build reliable data pipelines using Python and SQL
- →Architect a data warehouse using modern tools (dbt, BigQuery, or Supabase)
- →Implement data quality monitoring and testing
- →Orchestrate workflows using Apache Airflow or Prefect
- →Understand data infrastructure cost, reliability, and governance trade-offs
Machine Learning
▲ Advanced● Enrolling nowBuild machine learning systems that work in production — not just in notebooks. This track covers the full ML lifecycle from problem framing to deployment, with an emphasis on rigorous evaluation and knowing when machine learning is not the right answer.
- →The most demanding track we run (12–15 hours/week) — production ML, not notebook demos.
- →A strong Python and statistics foundation is assumed and will be tested.
- →Entry is by application: either complete Data Engineering, or pass a placement assessment that proves equivalent experience.
Advanced tracks are open for enrolment now, but you must complete the prerequisite track first. If you already have the experience, you can sit a placement assessment to verify it and enter the advanced track directly — no one skips the prerequisite on an unverified claim.
- →Frame business problems as machine learning problems — and know when not to
- →Build, train, and evaluate supervised and unsupervised models
- →Implement the full ML lifecycle: data → model → evaluation → deployment
- →Monitor models in production and detect when they degrade
- →Communicate model behaviour and limitations to non-technical stakeholders
Build something real, with a team.
A real, live product built with a cross-functional team — something you can show an employer, a client, or an investor.
From trained to earning.
The final month. Every graduate chooses a path and spends four weeks executing the specific steps that move them from trained to earning — each week with a real output that goes into the world.
Employment
Job search, applications, interviews. Target: first interview in 30 days, first offer in 60.
Freelancing
Platform setup, proposals, first paid clients. Target: first client within 45 days.
Startup
Validation, pitch, ecosystem. Target: one clear validation milestone within 30 days.
- ✓A complete, professional portfolio ready to show employers or clients
- ✓A configured professional presence — LinkedIn, GitHub, Behance, or equivalent
- ✓A written 90-day career action plan with weekly targets
- ✓At least one real career action before graduation
- ✓A track-specific E-Technix certificate