Course description

What you'll learn

• Write Python programs from scratch, using Git for version control and Docker for deployment.
• Understand how Large Language Models (LLMs) work: tokenization, embeddings, attention, and transformers.
• Design effective prompts: zero-shot, one-shot, few-shot, chain-of-thought, persona-based, and structured prompting.
• Implement Retrieval-Augmented Generation (RAG) pipelines with LangChain and vector databases.
• Understand Model Context Protocol (MCP) and build MCP servers with Python.

What will i learn?

• This course combines theory, coding, and deployment in one place. You’ll start from the basics of Python and Git, and by the end, you’ll be coding cutting-edge AI applications with LangChain, LangGraph, Ollama, Hugging Face, and more.
• Unlike other courses, this one doesn’t stop at “calling APIs.” You will go deeper into system design, queues, scaling, memory, and graph-powered AI agents — everything you need to stand out as an AI Engineer.

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