Python Programming for AI
4-6 weeksSkills You'll Build
Python fundamentals and syntaxPython testing frameworks (pytest, unittest)Object-oriented programming in PythonWorking with APIs and JSONVirtual environments and dependencies
QA Engineer → AI Engineer
QA Engineer to AI Engineer: Leverage Your Testing Mindset
A strategic roadmap for QA engineers transitioning to AI engineering. Your expertise in testing, edge cases, and quality assurance is exactly what AI systems need. Learn to apply your validation mindset to LLM evaluation, prompt testing, and building reliable AI applications.
5-8 months
Prerequisites
- Testing methodologies and frameworks
- Basic scripting (Python, JavaScript, or similar)
- Understanding of CI/CD pipelines
- Experience with test automation
- Analytical and systematic thinking
Your Learning Path
ML Fundamentals for QA Professionals
3-4 weeksSkills You'll Build
Understanding ML model lifecycleSupervised vs unsupervised learning conceptsModel inputs, outputs, and parametersData quality and preprocessing basicsUnderstanding model limitations
LLM APIs and Prompt Engineering
4-5 weeksSkills You'll Build
OpenAI and Claude API integrationPrompt engineering fundamentalsPrompt testing and iterationToken management and cost awarenessHandling API errors and edge cases
AI Testing and Evaluation
4-5 weeksSkills You'll Build
LLM output evaluation methodologiesBuilding test suites for AI systemsPrompt injection testing and securityRegression testing for AI applicationsAutomated evaluation pipelinesBenchmarking AI system performance
RAG Systems and Implementation
4-5 weeksSkills You'll Build
Embeddings and vector search conceptsRAG architecture and componentsDocument chunking strategiesRetrieval quality evaluationEnd-to-end RAG pipeline building
Portfolio and Career Transition
4-6 weeksSkills You'll Build
Building AI testing portfolio projectsAI quality assurance specialization positioningInterview preparation for AI rolesSalary negotiation strategiesNetworking in AI engineering community