What
You’ll Learn
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
Requirements
- A basic understanding of Python programming (variables
- functions
- loops)
- Familiarity with using Jupyter Notebooks or any Python IDE
- An interest in exploring how AI works through real-world projects
- A computer with at least 8GB of RAM and a stable internet connection
- (Optional) Basic knowledge of machine learning or data science concepts
- No prior AI/ML experience is required. This course will guide you from foundational topics to advanced projects step by step.
Description
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:
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LangChain, for chaining together LLM prompts and tools
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Ollama, to run local LLMs like LLaMA 3, Mistral, and Phi-2
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Streamlit and Gradio, for building interactive AI-powered web apps
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ChromaDB, for local vector search and RAG (Retrieval-Augmented Generation)
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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:
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Understand and apply machine learning and deep learning fundamentals
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Use transformers and pretrained LLMs in practical applications
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Build tools like AI chatbots, search engines, recommender systems, and speech agents
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Implement your own AI agents with memory, tools, reflection, and reasoning
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Evaluate models using your own LLM evaluation suite and red team test sets
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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.
Who this course is for:
- Aspiring AI engineers who want to build real-world projects and gain hands-on experience
- Developers and software engineers looking to transition into AI and machine learning
- Students and self-learners who want a structured
- project-based way to master AI
- Startup founders and tech entrepreneurs seeking to prototype AI-powered applications
- Educators and tech mentors who want ready-to-use projects to teach AI in practical settings
- Anyone curious about AI and motivated to learn by building instead of just reading theory
