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Master both sides of modern AI quality: use AI as an accountable assistant (testing with AI), and test AI-powered products with non-deterministic oracles, RAG checks, and safety gates (testing AI systems).
Ce cours comprend 50 labs pratiques — entraînez-vous dans de vrais environnements.
Haithem Mihoubi
Formateur
Cours gratuit
Inscription instantanée — toutes les leçons incluses
Ce cours inclut :
Master both sides of modern AI quality: use AI as an accountable assistant (testing with AI), and test AI-powered products with non-deterministic oracles, RAG checks, and safety gates (testing AI systems). This production-oriented phase combines written instruction, visual models, interactive decisions, and practical work on the shared QA Practice Hub application from manual testing through automation and SDET practices.
-67%En vedetteGo from the agentic loop to governed, production multi-agent systems: tool use, planning, memory, MCP, agentic RAG, multi-agent orchestration, safety, sandboxing, observability, and enterprise deployment.
Phase 21: AI for QA
Cours gratuit
Phase 21 walkthrough: AI tools for software quality (responsible use)
Using AI Responsibly
Limitations of AI
Human Validation
Privacy and Security
AI Evidence and Traceability
Prompt Engineering
Generating Test Cases
Generating Test Data
Bug Analysis
Log Analysis
Documentation Generation
Self Healing Locators
Visual AI Regression
AI Assisted Triage
Testing AI Systems
Non Deterministic Oracles
Prompt Regression
Evaluation Datasets
Model Evaluation
AI Output Quality
RAG Testing
Hallucination Detection
Adversarial Prompt Testing
Bias and Safety Testing
AI Agents for Quality Workflows
AI Governance
LLM Observability
AI in CI Quality Gates
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-67%En vedetteGo from first principles to running production NLP systems: tokenization, embeddings, transformers, fine-tuning, RAG, prompt engineering, alignment, evaluation, safety, and enterprise-grade serving.
-67%En vedetteGo from first principles to running a production ML platform: data versioning, feature stores, CI/CD/CT, Kubernetes serving, monitoring, drift detection, security, cost, LLMOps, and incident response.
En vedetteA 180-hour beginner-to-expert AI engineering program covering software, data, ML, deep learning, vision, NLP, LLMs, RAG, agents, MCP, MLOps, cloud, security, architecture, and AI SaaS.