🎓
AI Fundamentals
Understand how LLMs work and what they can do
16 resources
30-40 hours
12 beginner · 2 intermediate · 2 advanced
16 resources
🎯 Start Here
Perfect for beginners or those new to this topic
video
beginner
Intro to Large Language Models
Andrej Karpathy
1 hour
General-audience introduction to LLMs covering what they are, how they work, where they're headed, and security challenges. Explains LLMs as the core component behind ChatGPT, Claude, and Bard with operating system analogies.
Updated: November 2023
interactive
beginner
Prompt Engineering Interactive Tutorial
Anthropic
2-3 hours
Hands-on Jupyter notebooks teaching production-grade prompting with Claude. Nine chapters covering prompt structure, common pitfalls, Claude's strengths/limitations, and crafting effective prompts. Interactive exercises throughout.
Updated: 2024
guide
beginner
Prompt Engineering Guide
Anthropic
30 min read
Official documentation on prompt engineering best practices for Claude 4.x models. Covers clear instructions, providing context, using examples, chain-of-thought reasoning, and Claude 4 specific techniques.
course
beginner
Generative AI for Everyone
DeepLearning.AI (Andrew Ng)
3 hours
Non-technical course teaching how generative AI works and what it can (and can't) do. Hands-on exercises using generative AI in day-to-day work, with tips on effective prompt engineering. No coding required. Perfect for product managers and business leaders.
Updated: 2024
course
beginner
Deep Learning Specialization
DeepLearning.AI (Andrew Ng)
5 courses, ~25 hours
Comprehensive deep learning resource covering neural networks, CNNs, RNNs, and training techniques. Taught by Andrew Ng, Stanford adjunct professor and AI pioneer. Foundational concepts through advanced applications.
Updated: 2024
interactive
beginner
Tokenizer Tool
OpenAI
10 min
Interactive tool showing how text is converted to tokens. Essential for understanding costs, context limits, and prompt design. Visualizes tokenization for different models.
guide
beginner
Embeddings and Semantic Search
Cohere
30 min
Foundation for memory retrieval. Explains embeddings, semantic search, and how to implement them. Interactive examples included.
tutorial
beginner
Google AI Studio Quickstart
Google
30 minutes
Official getting started guide for Google AI Studio. Learn to prototype with Gemini models in browser, use multimodal prompts, generate code, and export to Gemini API. No setup required—build immediately.
Updated: 2025
tutorial
beginner
GitHub Spark: Build Apps with Natural Language
GitHub
20 minutes
Get started with GitHub Spark to build full-stack web apps using natural language. Learn to describe what you want, iterate through conversation, preview instantly, and deploy with one click. Own all your code.
Updated: 2025
tutorial
beginner
NotebookLM: Research Assistant Guide
Google
30 minutes
Learn to use NotebookLM as your AI research assistant. Upload sources (PDFs, docs, videos), generate summaries and study guides, and create Audio Overviews (AI-generated podcasts). Ground AI responses in your materials.
Updated: 2025
tutorial
beginner
Gemini API Quickstart
Google
30 minutes
Official quickstart for Gemini API with 2M token context. Learn to use multimodal capabilities (text, images, video), implement function calling, and optimize for long-context use cases. Multiple language SDKs available.
Updated: 2025
course
beginner
ChatGPT Prompt Engineering for Developers
DeepLearning.AI (Andrew Ng & OpenAI)
1 hour
Short course teaching prompt engineering best practices from OpenAI and Andrew Ng. Learn to build applications with LLMs: summarization, inferencing, transformation, expansion, and chatbots. Hands-on coding examples in Python. Free course.
Updated: 2024
🚀 Core Concepts
Dive deeper into the fundamentals and best practices
course
intermediate
Neural Networks: Zero to Hero
Andrej Karpathy
~15 hours
Build neural networks from scratch in code. Starts with backpropagation basics and builds up to modern deep neural networks like GPT. Language models as the entry point to deep learning, fully transferable to other domains.
paper
intermediate
Chain-of-Thought Prompting
Google Research
20 min read
Shows how prompting language models to explain their reasoning step-by-step dramatically improves performance on complex tasks. Foundation for making LLMs reason.
Updated: 2022
🔥 Advanced Topics
For experienced practitioners looking to go deeper
paper
advanced
ReAct: Synergizing Reasoning and Acting
Princeton/Google Research
30 min read
Foundational agent pattern combining reasoning traces and task-specific actions. Shows how language models can generate reasoning traces and actions in an interleaved manner. Most production agents use this pattern.
Updated: 2022
paper
advanced
Attention Is All You Need
Google Research
45 min read
The transformer architecture paper. Foundation of all modern LLMs (GPT, Claude, Gemini). Introduced the attention mechanism that powers language models.
Updated: 2017
📄 Key Papers
Foundational research papers that shaped this field
paper
advanced
ReAct: Synergizing Reasoning and Acting
Princeton/Google Research
30 min read
Foundational agent pattern combining reasoning traces and task-specific actions. Shows how language models can generate reasoning traces and actions in an interleaved manner. Most production agents use this pattern.
Updated: 2022
paper
intermediate
Chain-of-Thought Prompting
Google Research
20 min read
Shows how prompting language models to explain their reasoning step-by-step dramatically improves performance on complex tasks. Foundation for making LLMs reason.
Updated: 2022
paper
advanced
Attention Is All You Need
Google Research
45 min read
The transformer architecture paper. Foundation of all modern LLMs (GPT, Claude, Gemini). Introduced the attention mechanism that powers language models.
Updated: 2017
What to Learn Next
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