Bafoussam · Next cohort: January 2027

Learn to build. Build to last.

Hands-on training, taught by engineers who build and run products in production.

Workshop Hands-on projects ✦ Applied AI

Tracks

Choose your path.

Full-stack web development

From front end to database, all the way to production.

Mobile development

iOS and Android apps with React Native.

Applied AI engineering

Bringing artificial intelligence into real products.

AI at work

For non-technical professionals who want to use AI every day.

Corporate training

Tailored programmes for your teams.

Artificial intelligence

AI is learned by building.

Artificial intelligence is already changing how people write, analyse, code and serve their customers. We teach it the way we use it every day: in real products, with real constraints on cost, quality and privacy.

  1. Understand

    What models can do, what they can’t, and why they sometimes get things wrong.

  2. Practise

    Every concept is applied straight away, on cases taken from real work.

  3. Build

    Every track ends with a concrete, useful project you can show.

Applied AI engineering

Bring AI into real applications, reliably and under control.

Who it’s for
Developers, computer science students and engineering teams.
Prerequisites
You can already program (JavaScript, PHP or Python).

What you’ll learn

  1. How large language models work

    Tokens, context, temperature, limits and hallucinations: the basics for making the right choices.

  2. Designing good prompts

    Instructions, examples, roles and structured JSON outputs your code can use directly.

  3. Calling a model from an app

    APIs, streaming, error and timeout handling, in a Laravel, Node.js or React Native app.

  4. RAG: answering from your documents

    Chunk, index and retrieve information (embeddings, vector search) for answers that cite their sources.

  5. Agents and tools

    Give the model tools to call (APIs, databases, search) and set limits on what it is allowed to do.

  6. Evaluating and testing

    Test sets, quality criteria and version comparisons, so you know whether a change really improves results.

  7. Going to production

    Cost, latency, caching, monitoring and logs: running an AI feature over time.

  8. Security and privacy

    Prompt injection, data leaks, access control: protecting your users and your business.

By the end You can design, build, evaluate and ship an AI feature in a real application.

AI at work

Use AI every day to save time, without writing a line of code.

Who it’s for
Professionals, entrepreneurs, teachers, administrative and sales staff.
Prerequisites
You can use a computer and the internet.

What you’ll learn

  1. Getting started with an AI assistant

    What it can do, its limits, and how to phrase a request to get a useful result.

  2. Writing, rewording, summarising

    Emails, reports, meeting notes, letters and posts, in French and in English.

  3. Analysing documents and data

    Pull the essentials out of a long document, query a spreadsheet, prepare a summary with figures.

  4. Researching and checking

    Use AI to search, then check facts and sources before relying on them.

  5. Presentations and visuals

    Structure a presentation, prepare slides and simple visuals.

  6. Automating repetitive tasks

    Reusable request templates and small automations, without programming.

  7. Privacy at work

    What you can share with an AI tool, what you never share, and good team practices.

By the end You use AI in your everyday work, methodically and safely.

What you’ll build

Projects grounded in real life.

An assistant for your documents

It answers questions about your procedures, contracts or rules, quoting the passage it used.

A customer assistant on WhatsApp

It answers frequent questions and hands over to a person when needed.

Automatic invoice extraction

The details of an invoice or receipt, read and organised into a table.

Sorting incoming messages

Requests classified by topic and urgency, then routed to the right person.

A dashboard that explains itself

Figures with a clear written summary, ready to share.

Your own automation

One process from your work, redesigned with AI, from need to result.

Responsible AI

Powerful, when used well.

  • Check what AI produces before using it.
  • Protect personal and confidential data.
  • Keep a person accountable for important decisions.
  • Recognise and correct bias.
  • Cite your sources and stay transparent with your customers.

AI for companies

Use cases in your own processes.

We start from your business: a workshop to find where AI saves time, then training tailored to your teams and tools, with the privacy rules that go with it.

Frequently asked questions

AI at the Academy.

Do I need to know how to code?

Not for “AI at work”, designed for non-technical profiles. Yes for “Applied AI engineering”, which expects you to already program.

How long do the programmes last?

From 3 months to 2 years, depending on the track.

When does the next cohort start?

In January 2027, in Bafoussam.

Which tools will we use?

The main AI assistants and APIs on the market, as well as open-source models. We teach methods that stay valid as the tools change.

Can companies train their teams?

Yes. We build a tailored programme from your use cases, at your offices or ours.

Format

Learn by building.

Real projects, code reviews and mentoring from working engineers.

From 3 months to 2 years, depending on the track.

Admission

How to join.

  1. Apply Tell us who you are and what you want to learn.
  2. Talk A conversation to choose the right track.
  3. Enrol Join the next cohort.

For companies

Train your teams.

Development, digital tools or AI applied to your business: we build a programme around your teams, at your offices or ours.

Join the next cohort.

Leave your details and we’ll get back to you as soon as enrolment opens.

Next cohort: January 2027