Free Download Full Stack Generative AI: Deep Learning, CNN, LLM Agentic AI
Published 8/2025
Created by Abhilash Nelson
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 186 Lectures ( 24h 39m ) | Size: 16.5 GB
Python, NumPy, Pandas, Matplotlib, Deep Learning, Generative AI : GAN, VAE, LLMs, RAG, MCP, ACP, A2A, Agentic AI & more
What you'll learn
Design and implement Generative AI models such as GANs, VAEs, Diffusion Models, and Large Language Models, including Retrieval-Augmented Generation (RAG).
Build autonomous AI agents using Agentic AI frameworks like LangChain and apply protocols such as MCP, ACP, and A2A
Understand and train deep learning models, building a strong foundation for advanced AI concepts.
Write Python programs and perform data manipulation and visualization using NumPy, Pandas, and Matplotlib.
Requirements
No prior programming or AI experience is required, this course starts from the basics. A basic understanding of high school mathematics (algebra, probability, and functions) will be helpful. Access to a computer with an internet connection. Curiosity, consistency, and a willingness to learn by building hands-on projects.
Description
This comprehensive course is your one-stop guide to learn Python Basics, Popular Data Manipulation Libraries, Deep Learning Fundamentals, Popular Generative AI Models, Large Language Models and Agentic AI frameworks, all in one place. Whether you're a beginner exploring the world of AI or a developer looking to level up, this course takes you from the ground up and beyond.We begin with Python fundamentals and dive into essential data libraries like NumPy, Pandas, and Matplotlib for effective data handling and visualization. Then, we advance into Deep Learning, building and training neural networksMode to understand the core mechanics behind AI.Generative AI is a subset of Deep Learning. Without a solid understanding of Deep Learning fundamentals, learning Generative AI becomes difficult and often confusing. That's why I've combined the most essential parts from one of my previous Deep Learning courses into this course. This ensures that you build a strong foundation before diving into advanced Generative AI topics.Once the Deep Learning Fundamentals is complete, You'll then explore the rapidly evolving field of Generative AI:From training your own GANs and VAEs, to working with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Diffusion Models, this course offers hands-on projects and intuitive explanations.Finally, we introduce you to the next frontier: Agentic AI. Learn about intelligent agent architectures such as MCP, ACP, and A2A, and use cutting-edge frameworks like LangChain to build autonomous, goal-driven AI agents.What You'll LearnPython programming basics and data manipulation using NumPy and PandasData visualization using MatplotlibFundamentals of Deep Learning and neural network trainingBuilding Generative AI models: GANs, VAEs, LLMs, and Diffusion ModelsImplementing Retrieval-Augmented Generation (RAG)Understanding and applying Agentic AI Protocols: MCP, ACP, A2AWorking with popular Agentic AI frameworks like LangChainRequirementsNo prior programming or AI experience is requiredA basic understanding of high-school math is helpfulAccess to a computer with internet connectionCuriosity and a willingness to learn by building real-world projectsThe code, and jupyter notebook files used in this course has been uploaded and shared in a folder. I will include the link to download them in the last session or the resource section of this course. You are free to use the code in your projects with no questions asked.Also after completing this course, you will be provided with a course completion certificate which will add value to your portfolio.So that's all for now, see you soon in the class room. Happy learning and have a great time.
Who this course is for
Beginners who want to start their journey in Python programming, AI, and Generative AI. Students and professionals who want to build a strong foundation in Deep Learning before diving into advanced AI models. Developers and data enthusiasts looking to upskill in Generative AI, LLMs, and Agentic AI frameworks. Researchers, hobbyists, and innovators interested in building real-world AI projects and autonomous AI agents.
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