LLM Fundamentals & API Integration
2-3 weeksSkills You'll Build
OpenAI and Claude API integrationPrompt engineering for productionToken management and cost optimizationStreaming responses and async handling
Python Developer → AI Engineer
Python Developer to AI Engineer: The Fastest Transition Path
You already have the hardest skill in the bag - Python fluency. This is the fastest path to AI engineering, typically 2-4 months. While others struggle with Python basics, you'll dive straight into LLM APIs, RAG systems, and production deployment. Your existing skills in API development, data handling, and testing transfer directly to AI applications.
2-4 months
Prerequisites
- Python proficiency (classes, decorators, async/await)
- Package management (pip, virtualenv, or conda)
- Basic API development (Flask, FastAPI, or Django REST)
- Data handling (JSON, CSV, basic Pandas)
- Version control (Git)
Your Learning Path
Embeddings & Vector Databases
2-3 weeksSkills You'll Build
Text embeddings generationVector database setup (Pinecone, Chroma, pgvector)Semantic search implementationHybrid search strategies
RAG Systems Development
3-4 weeksSkills You'll Build
Document chunking strategiesRetrieval pipeline architectureContext window optimizationRAG evaluation and iteration
Production Deployment & Architecture
2-3 weeksSkills You'll Build
FastAPI for AI applicationsDocker containerization for AIAPI rate limiting and cachingError handling and monitoring
Portfolio & Job Search
2-3 weeksSkills You'll Build
AI project portfolio developmentTechnical interview preparationSystem design for AI applicationsSalary negotiation strategies