PH_wp_[FR]_Academy_Tendances evolutions banner

ACCELERATE YOUR TESTING WITH AI

Compliance with the profession - Methods

general information

goals:

This training course will enable you to:

Gain a comprehensive understanding of generative AI for testing
Learn effective querying techniques
Discover and experiment with AI tools for testing :

⇒ Anthropic / Claude 3
⇒ GPT 3.5 and GPT 4 (OpenAI)
⇒ Mistral Small and Mistral Medium (Mistral)
⇒ LLM workbench, Application RAG, and Gravity platform (Smartesting)
⇒ CodeLLama (Meta)
⇒ Sonar Small and Sonar Medium (Perplexity)
As technologies evolve, this list will evolve according to what is most relevant.

Identifying the limits and risks of AI-enhanced testing

profile Targeted:

Consultant Testing
Tester
Developer
Project Manager
Test Automator
Product Owner
Project manager
Quality engineer
QA Manager

Mandatory requirements :

Software testing experience (at least at a first level)

introduction:

1. Generative AI for software testing: Introduction

Generative AI - The basics
What generative AI brings to software testing
Using generative AI for testing, general principles (workshop on using the LLM portal for training)

2. Prompt engineering - Requesting a large language model for testing: how to get good results

Introduction to Prompt Engineering
Prompting techniques and best practices
Use cases with practical exercises in 4 workshops: improving existing test cases, test case design, test automation, analyzing anomaly reports
Plus: tools to help you create your own prompts
Debriefing and discussion of the skills implemented

3. Managing the risks of generative AI

My AI is wrong: how to detect AI errors / evaluation metrics (workshop)
My AI doesn't protect my data: managing this risk, what solutions?
My AI is biased: concrete examples, how to avoid it
Other AI-related risks
Environmental risks (workshop on energy costs)
Evolution risks
AI regulation (European AI Act)

4. LLM-based test applications

LLM-based applications: LLMOps,
Workshop on Retrieval Augmented
Generation (RAG) - Q/R on a large document corpus, LLM Fine-Tuning
Integrating LLM-based functions into
testing tools: workshop on integrating generative AI functions into a testing tool
Autonomous AI agents for testing with demonstration: Gérald - Virtual Manual
Tester
Summary and discussion

5. Advanced techniques for using generative AI in software testing

LLM-based applications
Adapting an AI model to test tasks: fine-tuning
AI agent testing: towards autonomous or semi-autonomous testing

6. Synthesis: what we've learned

I'll start using tomorrow: how do I go about it in practice?
I choose my generative AI model for testing

Teaching methods:

35% theory
75% practive : 9+ Workshops & Exercises

Terms of evaluation:

None

TRAINING PARTNER:

Our course is in partnership with avec Smartesting.

Next sessions

19/01/2026 - 20/01/2026 · Remote
05/02/2026 - 06/02/2026 · Remote
16/03/2026 - 17/03/2026 · Remote

See all the dates available

2 days (14h of training)

On demand

Available in FR, EN or DE

Next sessions

Filter by location

19/01/2026 - 20/01/2026 · Remote
05/02/2026 - 06/02/2026 · Remote
16/03/2026 - 17/03/2026 · Remote
02/04/2026 - 03/04/2026 · Remote
18/05/2026 - 19/05/2026 · Remote
18/06/2026 - 19/06/2026 · Remote
21/09/2026 - 22/09/2026 · Remote
08/10/2026 - 09/10/2026 · Remote
19/11/2026 - 20/11/2026 · Remote
07/12/2026 - 08/12/2026 · Remote

ACCELERATE YOUR TESTING WITH AI

general information

goals:

profile Targeted:

Mandatory requirements :

Teaching methods:

Terms of evaluation:

TRAINING PARTNER:

Next sessions

Accelerate your testing with AI

Discover our other classes about trends and evolutions in software testing