AI Learning Center Encyclopedia
A comprehensive, university-grade AI curriculum from first principles to frontier engineering. Every lesson features dual reading depths: General (intuitive 8th-grade explanations and myths) and Technical (math, code labs, and research citations). Explore 29 structured courses and 300 in-depth lessons.
Choose Your Pathway
Select a tailored pathway based on your background and goals, or browse the complete 29-course catalog below.
Curious Explorer
Build fundamental AI literacy: definitions, history, LLM basics, prompt engineering, and real-world limits.
AI Systems Builder
Master engineering implementations: neural networks, tokenization, transformers, RAG, tool calling, and agents.
Advanced AI & Research
Deep dive into production systems: reinforcement learning, causal DAGs, MLOps, red teaming, and robotics.
Founder & Executive
Navigate commercial reality: role playbooks, compute economics, API service terms, and UI design.
All 29 Courses (300 Lessons)
Every course is modular and free. Click any course to view its complete unit syllabus and lessons.
What AI Actually Is
Clear, foundational definitions of what artificial intelligence actually is, how it evolved, its real capabilities, and its hard boundaries—with zero hype.
Data, Labels and Reality
How data, labels, distributions, and real-world annotations power models—and why messy data, leakage, and sampling skew create messy results.
Machine Learning Core
The core foundations of machine learning: supervised learning, classification, regression, loss functions, decision trees, and generalization.
Math for AI
Essential mathematical intuition for AI: linear algebra, vectors, matrices, eigenvalues, gradients, optimization, and probability distributions.
Neural Networks and Deep Learning
Deep learning architectures: artificial neurons, activation functions, backpropagation, CNNs, RNNs, and the dawn of attention mechanisms.
Classical AI
Timeless classical AI methods: state-space search, heuristics, A*, minimax, constraint satisfaction problems, and Bayesian networks.
Language Models and Transformers
The modern engine of AI: transformers, multi-head self-attention, tokenization, embeddings, pretraining, fine-tuning, and Mixture of Experts (MoE).
Prompting, Use and Verification
Mastering model steerability: prompt engineering patterns, structured output formatting, chain-of-thought, hallucination reduction, and verification workflows.
RAG, Search and Knowledge Systems
Building reliable knowledge-grounded systems: document chunking, dense embeddings, hybrid BM25 search, rerankers, citations, and graph RAG.
Agents and Tool-Using Systems
Autonomous systems that loop: tool calling, function interfaces, short and long-term memory, multi-step planning, and human-in-the-loop safety gates.
Generative Media
Creative media synthesis: diffusion models, text-to-image architectures, video generation, temporal consistency, audio generation, and authenticity watermarking.
Computer Vision
Teaching machines to perceive: object detection, semantic and instance segmentation, optical character recognition (OCR), and vision-language models (VLMs).
Speech and Audio
Acoustic modeling and sound: speech recognition (ASR), audio event detection, text-to-speech (TTS), and open toolkits (Kaldi, ESPnet, SpeechBrain).
Reinforcement Learning
Learning through interaction and reward: Markov Decision Processes (MDPs), Q-learning, policy gradients, PPO, and Reinforcement Learning from Human Feedback (RLHF).
NLP Beyond Chatbots
Text understanding beyond chat: Named Entity Recognition (NER), machine translation, document-level information extraction, and summarization evaluation.
Probabilistic Models and Causality Lite
Distinguishing correlation from causation: causal Directed Acyclic Graphs (DAGs), confounding, d-separation, interventions, and identification strategies.
Data Systems, MLOps and Production
Operating ML in production: feature stores, training-serving skew, model registries, automated data validation, drift monitoring, and technical debt.
Evaluation, Benchmarks and Red Teaming
Rigorous evaluation and adversarial testing: capability benchmarks, safety eval suites, automated red-teaming (HarmBench), and proxy vs gold metrics.
Safety, Security, Bias and Alignment
Architecting resilient systems: prompt injection defense, sandboxing, data minimization, algorithmic fairness, and secure software lifecycles.
Society, Law, Policy & Work
Civic and policy literacy: labor economics, academic integrity in education, synthetic media disclosure, EU AI Act, and global governance frameworks.
Coding Labs (Python)
Hands-on Python implementations: building mini-RAG systems, image classifiers, text embeddings pipelines, and bounded agent execution loops.
Role Playbooks
Targeted AI workflows and operating playbooks for founders, software engineers, educators, product designers, and creative directors.
Research Literacy and Self-Study
Empowering independent research: how to dissect arXiv preprints, audit claims against experimental evidence, understand ablations, and spot reproducibility gaps.
Hardware, Compute and Energy
The physical reality of AI: GPUs, TPUs, custom ASICs, memory bandwidth constraints, quantization, edge vs cloud inference, and datacenter energy footprint.
Open Source, Vendors and Ecosystem
Navigating the industry landscape: open weights vs open source, software and model licenses, API service terms, hosting trade-offs, and portability.
Human-AI Interaction and Product Design
Designing human-centered AI interfaces: calibrated user trust, uncertainty display, mixed-initiative workflows, 18 HAX guidelines, and PAIR patterns.
Robotics and Embodied AI (Intro)
Embodied intelligence: spatial perception, robot kinematics, ROS2 middleware, simulation-to-real transfer, and Vision-Language-Action (VLA) models.
Reference and Maps
Comprehensive navigation aids: cross-link index, mathematical formula reference sheets, study roadmaps, and capstone project ideas.
The Dangers of AI
Public safety literacy: direct and indirect prompt injection, scam awareness, voice clones, and nonconsensual synthetic media defenses—without attack recipes.