Certificates That
Mean Something.

Awarded to students who complete the Data Analytics track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the Web App Development track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the Mobile & Desktop Apps track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the AI & Agentic Systems track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the Product Design track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the Digital Entrepreneurship track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the AI Product Management track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the Cybersecurity Fundamentals track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the Data Engineering track and prove the skills below through a real capstone project — not an exam.

• 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

Awarded to students who complete the Machine Learning track and prove the skills below through a real capstone project — not an exam.

• 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