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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 :
  1. ⇒ Anthropic / Claude 3
  2. ⇒ GPT 3.5 and GPT 4 (OpenAI)
  3. ⇒ Mistral Small and Mistral Medium (Mistral)
  4. ⇒ LLM workbench, Application RAG, and Gravity platform (Smartesting)
  5. ⇒ CodeLLama (Meta)
  6. ⇒ Sonar Small and Sonar Medium (Perplexity)
  7. 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.

 

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Next sessions
  • 27/01/2025 - 28/01/2025 · Remote
  • 10/03/2025 - 11/03/2025 · Remote
  • 31/03/2025 - 01/04/2025 · Remote
See all the dates available
icon-time 2 days (14h of training)
icon-salary On demand
icon-training-1 Available in FR, EN or DE

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  • 27/01/2025 - 28/01/2025 · Remote
  • 10/03/2025 - 11/03/2025 · Remote
  • 31/03/2025 - 01/04/2025 · Remote
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