Udemy

AI Bible: From Beginner to Builder in 100 Projects

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  • 14,455 Students
  • Updated 6/2025
  • Certificate Available
4.1
(111 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
3 Hour(s) 8 Minute(s)
Language
English
Taught by
Gourav J. Shah, School of AI
Certificate
  • Available
  • *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4.1
(111 Ratings)

Course Overview

AI Bible: From Beginner to Builder in 100 Projects

Master AI by building 100 real-world projects using Python, LLMs, agents, tools like LangChain, Ollama, and Streamlit

Welcome to the AI Bible — your ultimate, hands-on guide to mastering artificial intelligence through 100 real-world projects. This isn’t just another theory-heavy AI course. It’s a practical, immersive journey designed to help you learn AI by building, from day one.

Whether you’re a beginner, a self-taught developer, or a seasoned engineer looking to pivot into the AI space, this course gives you the tools, confidence, and structure to go from zero to building production-ready AI applications. You’ll not only gain an understanding of core concepts like machine learning, deep learning, natural language processing, and computer vision, but you’ll actually use them to create projects that solve real problems.

Over 100 days, you’ll work on 100 standalone projects that cover everything from basic AI models to cutting-edge systems involving LLMs, agents, tool use, voice processing, search, memory, and multi-agent orchestration. Each project comes with clear code, explanations, and ideas for customization—making it the perfect resource for portfolio building, interviews, or startups.

You’ll explore and integrate powerful open-source tools including:

  • LangChain, for chaining together LLM prompts and tools

  • Ollama, to run local LLMs like LLaMA 3, Mistral, and Phi-2

  • Streamlit and Gradio, for building interactive AI-powered web apps

  • ChromaDB, for local vector search and RAG (Retrieval-Augmented Generation)

  • CrewAI and LangGraph, to build advanced multi-agent systems

Unlike most courses, you won’t be dependent on cloud APIs. This curriculum emphasizes offline, local AI development, ensuring you learn to build powerful applications with full data privacy, portability, and control.

By the end of this course, you will:

  • Understand and apply machine learning and deep learning fundamentals

  • Use transformers and pretrained LLMs in practical applications

  • Build tools like AI chatbots, search engines, recommender systems, and speech agents

  • Implement your own AI agents with memory, tools, reflection, and reasoning

  • Evaluate models using your own LLM evaluation suite and red team test sets

  • Develop an ethical AI mindset by writing your own AI Manifesto and alignment strategy

This course is also a reflection on how we build AI: the final project asks you to create a Personal AI Manifesto, helping you align your skills with the kind of world you want to create.

Whether you want to become an AI engineer, launch your own AI startup, or just understand the technology shaping the future, the AI Bible gives you everything you need—one project at a time.

Course Content

  • 8 section(s)
  • 40 lecture(s)
  • Section 1 Foundations of Artificial Intelligence
  • Section 2 Core Domains of AI
  • Section 3 Tools, Frameworks, and Infrastructure
  • Section 4 Agentic AI and Autonomous Systems
  • Section 5 Real-World Applications
  • Section 6 Ethics, Safety, and Philosophy
  • Section 7 The Future of AI
  • Section 8 100 AI Projects - Step-by-Step Instructions

What You’ll Learn

  • Build and deploy 100 practical AI and ML projects from scratch
  • Understand core concepts in NLP, computer vision, and agents
  • Use libraries like PyTorch, TensorFlow, HuggingFace, and LangChain
  • Create AI apps with Streamlit, FastAPI, and Gradio
  • Fine-tune LLMs and build RAG and agentic systems locally
  • Apply AI in real-world domains: health, finance, education, etc.
  • Integrate speech, image, and text models into full-stack apps
  • Evaluate and test LLMs for safety, alignment, and accuracy
  • Use tools like ChromaDB, Ollama, and LangGraph offline
  • Develop ethical, aligned, and human-centered AI systems


Reviews

  • D
    Daír Sánchez
    1.0

    Just theory, the instructor just read some theory and thats all, the examples are too easy, this is not a bible

  • J
    James Byers
    4.0

    Good material on the slides and verbally. Awesome resources! The only issue is that the AI voice occasionally says random words at the beginning of each video.

  • D
    Dmytro Rumyantsev
    2.0

    Not a Bible, not a course - just vocalized superficial presentation without any explanation of AI math and logic. In general, it is a crib with 100 AI project templates of unknown origin... in PDF format.

  • S
    Someswaran Prithiviraj
    3.0

    I truly appreciated the 100 hands on projects. They were very practical, well designed, and gave me a strong sense of real world applications. They made the learning experience very impact full and exciting. However, the concept explanations fell short. the use of plain, static slides often made it hard to follow or absorb key ideas. More engaging formats like animations, real world analogies, or live demos would significantly improve clarity and learning. Overall, excellent projects, but the teaching style could be more dynamic to match that high standard.

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