Course : Artificial intelligence for developers

Practical course - 3d - 21h00 - Ref. GIA
Price : 1980 € E.T.

Artificial intelligence for developers



New course

Artificial intelligence (AI) does not replace web developers. It complements them and helps them to develop tomorrow's web applications more rapidly. In this hands-on training course, you'll learn the methods and tools you need to make the most of this new form of machine control, and boost your productivity while controlling the various costs of AI tools.


INTER
IN-HOUSE
CUSTOM

Practical course in person or remote class
Disponible en anglais, à la demande

Ref. GIA
  3d - 21h00
1980 € E.T.




Artificial intelligence (AI) does not replace web developers. It complements them and helps them to develop tomorrow's web applications more rapidly. In this hands-on training course, you'll learn the methods and tools you need to make the most of this new form of machine control, and boost your productivity while controlling the various costs of AI tools.


Teaching objectives
At the end of the training, the participant will be able to:
Master the basics of AI computing architectures
IA tools for full-stack web developers
Prepare upstream prompts to create or modify a web application
Develop a web application with AI prompts and little casual development
Implementing fully local AI
Applying good development practices for AI

Intended audience
Web developers, integrators, software architects.

Prerequisites
Basic knowledge of HTML, CSS and JavaScript.

Practical details
Hands-on work
Des exercices et travaux pratiques permettront de mettre en œuvre les concepts abordés.
Teaching methods
Each new theoretical concept is immediately applied in practice.

Course schedule

1
Introduction to artificial intelligence

  • AI overview.
  • AI, machine learning, deep learning, symbolic versus statistical.
  • Large Language Model, text embeddings, transformers.
  • Natural Language Processing, GPT, Tokens.
  • Exploring the Vector Database and the GPT-Generated Unified Format (GGUF).
  • The main AI tools in SaaS mode.
  • LLM querying (prompt engineering).
  • Web architecture and AI.
Hands-on work
Avec l'aide d'un Large Language Model (LLM), écrire une application JavaScript qui relève un challenge d'IA symbolique comme la génération de grille de sudoku.

2
Visual Studio Code (VSCode) and GitHub Copilot

  • VSCode, GitHub Copilot, prerequisites for use.
  • GitHub Copilot chat.
  • Use Copilot directly from a file.
  • Define a function and its implementation.
  • Use a function.
Hands-on work
Write an application that generates web pages from a prompt sent to an LLM.

3
Programming by prompt

  • Why make full, detailed prompts?
  • Prompt writing techniques.
  • Role prompting, Few-Shot Prompting, Chain-of-thought (CoT).
  • Iteration, output format, Self-Consistency.
  • Negation, modularity, clarity and conciseness.
  • Strong and weak LLM coupling.
  • Transform your prompt into a web application.
  • Prompt for modification.
  • Prompt for all stages of a project.
  • Prompt ideation, specification, design, coding, testing, deployment.
Hands-on work
Make a web application specification prompt that gives the positive news of the day.

4
Cloud tools

  • Various cloud services (OpenAI, Claude, etc.).
  • API key management.
  • Tariff typology.
  • Development assistance : Lovable, Bolt.
  • GitHub Copilot, Windsurf, Continue.dev.
Hands-on work
Develop and deploy a web application using only an AI development assistant.

5
LLM

  • LLM architecture.
  • Use the concepts of temperature and top_p.
  • Features: summarization, classification, information extraction.
  • Structured JSON output format.
  • Study of the GGUP file.
  • LLMs on the market.
  • LLM on the Internet (SaaS).
  • Install LLM locally.
  • Introducing LM Studio and Hugging Faces.
  • Text embedding, cosine similarity, dimension reduction.
  • RAG architecture.
Hands-on work
Write a RAG (retrieval augmented generation) technical architecture specification for LLM exploring a local and confidential document database.

6
Tools for developing with AI

  • The OpenAI API.
  • Hugging Face: the GitHub of AI.
  • LLM, transformers, datasets.
  • LangChain: API for AI.
  • LM Studio: running AI components locally.
  • Best practices in tool use.
Hands-on work
Make a local "ChatGPT" that explores a confidential document base with a RAG architecture.


Customer reviews
4,1 / 5
Customer reviews are based on end-of-course evaluations. The score is calculated from all evaluations within the past year. Only reviews with a textual comment are displayed.
MATTHIAS D.
12/11/25
5 / 5

Very good, the course material is perhaps a little long, especially the introduction on the history of AI (but very well done).
BALTHAZAR C.
12/11/25
4 / 5

Jean Louis is a great trainer, I enjoyed the course and learned a lot from it. I would have emphasised the practical part in order to carry out and learn the theory, but overall I'm satisfied to have taken part in and followed this training course.
SÉBASTIEN C.
12/11/25
5 / 5

Jean-Louis, very good trainer for a first distance learning course :)



Dates and locations
Select your location or opt for the remote class then choose your date.
Remote class

Dernières places
Date garantie en présentiel ou à distance
Session garantie

REMOTE CLASS
2026 : 11 Feb., 1 July, 9 Sep., 21 Oct.

PARIS LA DÉFENSE
2026 : 4 Feb., 24 June, 2 Sep., 14 Oct.