The RAG Basics: From Documents to Cited Answers
Understand ingestion, chunking, retrieval, and grounded generation, with citations that constrain answers.
Python Runtime & Basics
A scenario-driven guide to Python Runtime & Basics, including boundaries, failure paths, and production trade-offs.
Python Data Structures & Decorators
A scenario-driven guide to Python Data Structures & Decorators, including boundaries, failure paths, and production trade-offs.
Python asyncio & Concurrency
A scenario-driven guide to Python asyncio & Concurrency, including boundaries, failure paths, and production trade-offs.
OpenAI API Fundamentals: Requests, Messages, Parameters, and Reliability
Build a reliable model API foundation with client setup, message structure, timeouts, retries, and cost controls.
LangChain Prompt Chains: Treat Prompts as Maintainable Programs
Use templates, variable contracts, message roles, and composition to build versioned and evaluable prompt chains.
LangChain Core Architecture: Runnables, Models, and Composable Chains
Understand how LangChain composes prompts, models, parsers, and Runnable stages into testable AI workflows.
FastAPI Request and Response Contracts with Pydantic
Use Pydantic schemas, field validation, response shaping, and consistent errors instead of fragile dictionary conventions.
FastAPI Project Architecture: Layering Routes and Domain Services
Organize a FastAPI service with layers, dependency injection, and configuration so AI endpoints stay testable and deployable.
AI Engineering with Python
A scenario-driven guide to AI Engineering with Python, including boundaries, failure paths, and production trade-offs.