One choice to make

Pick one. We teach the rest.

Three tracks run three months, all are free, and all end in a paid internship placement for qualified candidates. The difference is what you spend your evenings building.

Track 01

Artificial Intelligence

Build with the tools everyone is talking about

Prompting, automation, agents, and applied AI products. You leave able to ship a working assistant, not just talk about one.

What you leave with

  • Prompt engineering and model evaluation across frontier models
  • Automations that remove real hours of work using AI agents
  • Build and deploy an AI assistant end to end with memory and APIs
  • Retrieval-Augmented Generation and vector search for real business data
  • Fine-tuning, evals and responsible AI guardrails
  • Ship a portfolio product that solves a Nigerian problem
  • Halal-conscious, ethical use of AI at work and in products

Tools

Python basicsOpenAI / Gemini APIsn8nStreamlitGitLangChain / LangGraphPinecone / ChromaHugging FaceFastAPIReplicate
Apply to this track
Track 02

Data Science & Engineering

Move the data, then read what it says

Analytics and the pipelines behind it. You learn to model, clean and move data at scale, then turn it into dashboards and decisions a business can act on.

What you leave with

  • SQL to an advanced standard: joins, windows, CTEs, query tuning
  • Python for analysis: pandas, NumPy, visualisation and statistics
  • Data engineering: warehouse modelling, ELT pipelines, dbt and Airflow orchestration
  • Cloud storage and warehousing plus data quality, testing and documentation
  • BI dashboards leadership actually reads, and an intro to practical machine learning
  • A capstone: an end to end pipeline and dashboard on a real Nigerian dataset

Tools

ExcelSQL / PostgreSQLPython / pandasdbtApache AirflowBigQuery / SnowflakePower BIGit
Apply to this track
Track 03

DevOps & Cloud Engineering

Ship and scale the systems people rely on

A modern platform engineering path: Linux and networking foundations, containers, Kubernetes, infrastructure as code, CI/CD and observability, finished with a production grade deployment.

What you leave with

  • Linux, shell scripting, networking and Git workflows
  • Docker containers, image security and Kubernetes deployment on the cloud
  • Infrastructure as code with Terraform and configuration management with Ansible
  • CI/CD pipelines with GitHub Actions, plus GitOps delivery using Argo CD
  • Observability: Prometheus, Grafana, structured logging, alerting and incident response
  • Cloud and DevSecOps essentials: IAM, secrets management, cost control and reliability (SLOs)
  • A capstone: a containerised app deployed, automated, monitored and documented

Tools

Linux / BashGit / GitHubDockerKubernetesTerraformAnsibleGitHub ActionsArgo CDPrometheus / GrafanaAWS
Apply to this track

Still unsure?

Choose the one that sounds more like the work you want to be doing in a year. Month one is shared foundations across all tracks, so there is room to switch once before the split, just tell your coordinator.