COURSE DESCRIPTION
-
Write Python programs from scratch, using Git for version control and Docker for deployment.
-
Use Pydantic to handle structured data and validation in Python applications.
-
Understand how Large Language Models (LLMs) work: tokenization, embeddings, attention, and transformers.
-
Call and integrate APIs from OpenAI and Gemini with Python.
-
Design effective prompts: zero-shot, one-shot, few-shot, chain-of-thought, persona-based, and structured prompting.
-
Run and deploy models locally using Ollama, Hugging Face, and Docker.
-
Implement Retrieval-Augmented Generation (RAG) pipelines with LangChain and vector databases.
-
Use LangGraph to design stateful AI systems with nodes, edges, and checkpointing.
-
Understand Model Context Protocol (MCP) and build MCP servers with Python.
