Loading…
Loading…
Loading…
Make quality signals fast, reproducible, observable, and enforceable in delivery pipelines.
Dieser Kurs enthält 41 praktische Labs — üben Sie in echten Umgebungen.
Haithem Mihoubi
Dozent
Kostenloser Kurs
Sofort einschreiben — alle Lektionen inklusive
Dieser Kurs beinhaltet:
Make quality signals fast, reproducible, observable, and enforceable in delivery pipelines. 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.
Go 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 19: CI/CD for QA
Kostenloser Kurs
Phase 19 walkthrough: GitHub Actions and CI/CD pipelines
GitHub Actions
GitLab CI
Jenkins
Azure DevOps Pipelines
Docker
Docker Compose
Kubernetes
Selenium Grid
Selenoid
BrowserStack
Sauce Labs
AWS Testing
Azure Testing
Artifact Management
Secret Management
SonarQube
Quality Gates
Deployment Pipelines
Flaky Test Quarantine
Pipeline Observability
Noch keine Bewertungen. Seien Sie der Erste!
Schreiben Sie sich ein, um an der Diskussion teilzunehmen.
Noch keine Kommentare. Starten Sie die Diskussion!
Go from first principles to running production NLP systems: tokenization, embeddings, transformers, fine-tuning, RAG, prompt engineering, alignment, evaluation, safety, and enterprise-grade serving.
Go 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.
EmpfohlenA 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.