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Full stack generative and Agentic AI with python

Hands-on guide to modern AI: Tokenization, Agents, RAG, Vector DBs, and deploying scalable AI apps. Complete AI course
4.5 ★★★★★21,411 studentsCreated by Hitesh Choudhary, Piyush GargLast updated Dec 12, 2025🌐 English

What you'll learn

✓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.

Requirements

•No prior AI knowledge is required — we start from the basics.
•A computer (Windows, macOS, or Linux) with internet access.
•Basic programming knowledge is helpful but not mandatory (the course covers Python from scratch).

Description

Frequently Asked Questions

Student Feedback

4.5
★★★★★
Course Rating
75%
15%
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Sarah J.
★★★★★2 weeks ago

This course was absolutely amazing! The instructor explained everything clearly and the projects were very helpful.

M
Michael T.
★★★★1 month ago

Great content, highly recommended for beginners. Just wish there were more practice exercises.

D
David K.
★★★★★2 months ago

Best course on this topic I've taken so far. Worth every penny (even better since I got it for free!).

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Full stack generative and Agentic AI with python
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This course includes:
  • 📺 32h on-demand video
  • 📱 Access on mobile and TV
  • ♾️ Full lifetime access
  • 🏆 Certificate of completion