Course : Artificial intelligence for developers

Practical course - 3d - 21h00 - Ref. GIA
Price : 2320 CHF E.T.

Artificial intelligence for developers




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
Available in English on request

Ref. GIA
  3d - 21h00
2320 CHF 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.
CHRISTIAN B.
01/07/26
5 / 5

Cette formation en IA apporte une vraie valeur ajoutée opérationnelle. Les explications étaient précises, les échanges constructifs et les réponses aux questions toujours pertinentes. L’écoute du formateur, sa disponibilité et son expertise ont largement contribué à la réussite de cette formation.
DENIS D.
01/07/26
5 / 5

Formation très enrichissante et bien structurée. Le contenu était pertinent, clair et directement applicable, avec un bon équilibre entre apports théoriques et mise en pratique.
ASMAA E.
01/07/26
4 / 5

bonne explication, notions bien transmises



Dates and locations

Last places available
Guaranteed date, in person or remotely
Guaranteed session
From 9 to 11 September 2026 *
FR
Remote class
Registration
From 9 to 11 September 2026
FR
Remote class
Registration
From 21 to 23 October 2026 *
FR
Remote class
Registration
From 25 to 27 November 2026
FR
Remote class
Registration
From 16 to 18 December 2026
FR
Remote class
Registration

REMOTE CLASS
2026 : 9 Sep., 9 Sep., 21 Oct., 25 Nov., 16 Dec.