Full stack generative and Agentic AI with python — 90% Off Coupon

Hands-on guide to modern AI: Tokenization, Agents, RAG, Vector DBs, and deploying scalable AI apps. Complete AI course

4.5 30,485 students enrolledCreated by Hitesh Choudhary, Piyush GargLast updated: 🌐 English

Course Overview — Key Details

A quick-reference summary of the most important course details: provider, instructor, difficulty, duration, and what the coupon covers.

Course Title: Full stack generative and Agentic AI with python
Provider: Udemy (listed via CourseSpeak)
Instructor: Hitesh Choudhary, Piyush Garg
Coupon Verified On: February 6, 2026
Difficulty Level: All Levels
Category: Development
Subcategory: Generative AI (GenAI)
Duration: 32h of on-demand video
Language: English
Access: Lifetime Access · Mobile & TV compatible
Certificate: Certificate of completion included
Top Learning Outcomes: 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.
Prerequisites: No prior AI knowledge is required — we start from the basics. · A computer (Windows, macOS, or Linux) with internet access.
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What You'll Learn

Skills and competencies you'll gain from this Udemy course:

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.

Course Requirements & Prerequisites

Background knowledge or tools recommended before starting this course:

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).

About This Udemy Course

Full course description including curriculum, tools covered, and learning methodology:

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About the Instructor

This course is taught by Hitesh Choudhary, Piyush Garg. For full instructor bio, credentials, and other courses they teach, visit the instructor profile on Udemy.

Instructor: Hitesh Choudhary, Piyush Garg
Field: Development
Teaching Style: Practical, project-based learning (as described in course curriculum)

Is the Full stack generative and Agentic AI with python Coupon Worth It?

Full stack generative and Agentic AI with python is a development course offered on Udemy by instructor Hitesh Choudhary, Piyush Garg, spanning 32h of on-demand content. It holds a 4.5/5 rating from over 30,485 enrolled students.

Through CourseSpeak, you can access this course with a 90% discount coupon. The coupon was last verified on February 6, 2026. Udemy coupons are time-limited and claimed on a first-come basis — we recommend redeeming as soon as possible.

New to redeeming coupons? Visit our How to Redeem Udemy Coupon on CourseSpeak for detailed instructions on how to apply coupon codes.

✓ Our Take: Based on the rating (4.5/5) and enrollment numbers (30,485 students), this course appears well-regarded in its category. Use the coupon to access it at a significantly reduced price — and judge for yourself using Udemy's 30-day money-back guarantee.

Course Rating Summary

Aggregate rating data sourced from Udemy as of February 2026. For individual student reviews, visit the course page directly.

4.5
30,485 ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is estimated. For exact per-star counts, visit the Udemy course page.

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