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Cohort 1 applications are open until 1 December.Apply to the cohort (opens in a new tab)

Hard Skills Lab
FREN

Free data and AI training for young Africans

Real skills.Practical projects.A stronger tomorrow.

Hard Skills Lab trains young Africans in data and artificial intelligence, free and online, in French and English. We teach by doing, so you leave with a real project, not just theory.

  • Free
  • 8 weeks
  • 100% online
  • French & English
Apply to the cohort (opens in a new tab)See the curriculum
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The program

An 8-week cohort, two tracks, one goal.

You follow two tracks in parallel: Data Analysis with Python, and Artificial Intelligence & Machine Learning. Live sessions, hands-on exercises and a final capstone project.

  • 100% online

    Live sessions + self-paced work

  • Bilingual

    French & English

  • Beginner friendly

    No experience needed

  • Across Africa

    Open to young people across the continent

A coding class in a computer lab, with the teacher at the front

How it works

From application to final project.

  1. Apply

    Fill in the online form, in French or English. There is no fee.

  2. Learn live

    Each week, join one live data session and one live AI session.

  3. Practise

    Do the hands-on exercises at your own pace. Plan for about 10 to 12 hours a week in total.

  4. Present your project

    In weeks 7 and 8, bring both tracks together in one capstone project and present it.

The curriculum

8 weeks.2 tracks.1 project.

Everyone follows both tracks. Each week you have one data session and one AI session. The AI sessions only use Python you have already learned in the data track, so you can start from zero. In weeks 7 and 8, both tracks come together in one final project.

Tools you will use

  • Python
  • Jupyter
  • Google Colab
  • NumPy
  • pandas
  • Matplotlib
  • seaborn
  • scikit-learn

Data Analysis with Python

Led by Kokou Hugues Minasseh (LinkedIn profile, opens in a new tab)

Data scientist and educator

  1. 1Introduction and Python basics
  2. 2NumPy and data structures
  3. 3pandas fundamentals
  4. 4Data cleaning and preparation
  5. 5Exploratory data analysis
  6. 6Data visualisation
  7. 7Capstone: question, data and workflow
  8. 8Project presentation and discussion

By the end, you can

  • Write clear Python to load, clean and prepare messy data
  • Select, filter, group and reshape data with NumPy and pandas
  • Explore a dataset and back each finding with numbers
  • Build clear charts and present your findings in a notebook

Artificial Intelligence & ML

Led by Yao Gervais Amoah (LinkedIn profile, opens in a new tab)

Software engineer and educator

  1. 1What AI and ML are, no code yet
  2. 2How machines learn: features, labels, error
  3. 3First model: predicting a number
  4. 4Classification: predicting a category
  5. 5Better models: features, overfitting, comparison
  6. 6Finding groups and explaining results
  7. 7Generative AI, responsible AI, capstone plan
  8. 8Capstone: test, explain and present your model

By the end, you can

  • Explain in plain words how machines learn from data
  • Train and test regression and classification models
  • Compare models fairly and pick the right metric
  • Use generative AI responsibly and know a model's limits

The capstone: one project, both tracks

In weeks 7 and 8 you pick a real dataset on an issue you care about. You clean, explore and chart it with what the data track taught you, add one model from the AI track that predicts or groups something useful, then present your findings, the model's limits and one recommendation.

Real work

Sample projects

Two real projects from our team, one for each track, with the code open on GitHub. They show where the skills you learn here can take you.

  • Heatmap of road accidents in 2018 by day of the week and hour. The darkest cells are weekday mornings around 8:00 and late afternoons around 17:00.

    Data analysis project

    Example by our team

    When and where road accidents happen

    Cleaning and exploring the UK's 2018 road accident records to find the riskiest hours, roads and hotspots, then turning the results into road-safety advice. The worst hour is 17:00 and the worst day is Friday.

    Data: UK Department for Transport (STATS19), Open Government Licence v3.0.

    View on GitHub When and where road accidents happen (opens in a new tab)
  • Confusion matrices of two churn models on 1,000 test customers. The random forest classifies 977 correctly and the neural network 982.

    AI / ML project

    Example by our team

    Predicting which customers will leave

    Models that predict a streaming customer's monthly spend and whether they will cancel, compared with clear metrics, plus customer groups a retention team could act on. The best churn model was right for 98% of test customers.

    View on GitHub Predicting which customers will leave (opens in a new tab)

About us

Practical skills, open to the whole continent.

We believe African talent deserves practical, high-quality training in data and AI. Hard Skills Lab makes it free, online and project-first, so more young people can take part.

  • Free, so cost is not a barrier

    There are no fees. If you have the time and a stable connection, you can apply.

  • Bilingual, to reach most of the continent

    French or English is a working language in most African countries. Teaching in both opens the program to learners from francophone and anglophone countries.

  • Project-first, so you can show your skills

    You practise every topic and finish with a real project to add to your portfolio.

Good to know

Frequently asked questions

Something else? Write to us at contact@hardskills-lab.org

  • Is it really free?

    Yes. There are no fees to apply or to take part.

  • Do I need to know how to code?

    No. The program is beginner friendly. Week 1 starts with Python basics and setting up your tools, and the AI track begins without any code.

  • Who can join?

    Young people from anywhere in Africa who want to learn data and AI. No experience is needed.

  • Which language are classes in?

    French and English. The program runs in both languages, so learners from francophone and anglophone countries can join.

  • How much time does it take?

    About 10 to 12 hours a week for 8 weeks. That covers one live data session, one live AI session and practice at your own pace.

  • When does the next cohort start?

    Applications close on 1 December 2026. The start date is not set yet, and we will email you as soon as it is.

  • What do I get at the end?

    A real project that you built and presented, using what you learned in both tracks.

Join us

Ready to build your future?

Apply for the first cohort and take your first step into data and AI.

  • Eligibility

    Young people from anywhere in Africa.

  • Time commitment

    About 10 to 12 hours a week.

  • Internet

    A stable internet connection is required.

  • Application deadline

    1 December 2026

Apply to the cohort (opens in a new tab)

Have questions?

Get in touch with the team.

Contact us
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