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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 :
- ⇒ 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
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My AI is wrong: how to detect AI errors / evaluation metrics (workshop)
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My AI doesn't protect my data: managing this risk, what solutions?
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My AI is biased: concrete examples, how to avoid it
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Other AI-related risks
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Environmental risks (workshop on energy costs)
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Evolution risks
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AI regulation (European AI Act)
4. LLM-based test applications
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LLM-based applications: LLMOps,
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Workshop on Retrieval Augmented
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Generation (RAG) - Q/R on a large document corpus, LLM Fine-Tuning
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Integrating LLM-based functions into
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testing tools: workshop on integrating generative AI functions into a testing tool
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Autonomous AI agents for testing with demonstration: Gérald - Virtual Manual
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Tester
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Summary and discussion
5. Advanced techniques for using generative AI in software testing
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LLM-based applications
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Adapting an AI model to test tasks: fine-tuning
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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.
Request Enrollment
Submit your request - our team will follow up to confirm your seat.
Upcoming Sessions
All sessions are delivered in EN/FR. Minimum 3 participants required for a session to run.
