Loading…
Loading…
Loading…
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.
An LLM agent is a system that can execute tasks given in natural language or structured formats. It uses the planning capabilities of Large Language Models (LLMs) by calling tools that enable interaction with its environment. The agent also includes a memory mechanism. Both the agent's process and outcomes are non-deterministic.
LabsInspect, reproduce, and isolate failures across browsers, APIs, and distributed systems.
AI for QA
Cours gratuit
AI for QA 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
Aucun avis pour le moment. Soyez le premier !
Inscrivez-vous au cours pour participer à la discussion.
Aucun commentaire. Lancez la discussion !
En vedetteThe 19 FAANG coding-interview patterns plus an AI-era track (gradient descent, neural nets, transformers, tokenization, vector search, RAG, LLM decoding) — every topic with interactive step-through animations.
En vedetteLabsThe complete hands-on Docker course — 22 real terminal labs covering CLI, registries, Dockerfiles, networking, Compose, security, cleanup, production hardening, and a final interview exam. Built like KodeKloud.