IIISchool
School of Artificial Intelligence
The discipline of building, directing, evaluating, and governing intelligent systems.
The Academy treats AI as a discipline of engineering and judgment: how to build systems, how to instruct them, how to evaluate them, how to secure them, and how to know when they are wrong. Not a genre. Not a market. A working craft, taught with the same rigor as any older field of computer science, and read against the institutional questions the technology raises.
CreationKnowledge
- 101The History of AI21 lessons
- 102How LLMs Work31 lessons
- 103Prompt Engineering14 lessons
- 104Retrieval-Augmented Generation13 lessons
- 105Agents13 lessons
- 106AI APIs14 lessons
- 107Local AI and Local Models11 lessons
- 108AI Productivity8 lessons
- 109AI-Assisted Coding5 lessons
- 110Workflow Automation5 lessons
- 111Research with AI4 lessons
- 112AI in Business — Foundations5 lessons
- 201System Design for AI6 lessons
- 202Evaluation6 lessons
- 203Testing for AI Systems5 lessons
- 204Prompt Versioning4 lessons
- 205Observability5 lessons
- 206Cost and Latency5 lessons
- 207Caching and Prompt Caching4 lessons
- 208Memory Systems4 lessons
- 209Vector Databases7 lessons
- 210Guardrails and Safety Layers7 lessons
- 211Infrastructure and Scaling7 lessons
- 301Linear Algebra for ML6 lessons
- 302Probability for ML7 lessons
- 303Optimization and Gradient Descent6 lessons
- 304Feature Engineering5 lessons
- 305Regression5 lessons
- 306Classification6 lessons
- 307Neural Networks6 lessons
- 308CNNs5 lessons
- 309RNNs and Sequence Models3 lessons
- 310Transformers (Applied)4 lessons
- 311Embeddings and Representation Learning4 lessons
- 312Transfer Learning and Foundation Models4 lessons
- 401Hallucinations3 lessons
- 402Bias and Disparate Impact3 lessons
- 403Misuse3 lessons
- 404Copyright and Intellectual Property3 lessons
- 405Privacy3 lessons
- 406AI Security3 lessons
- 407Alignment6 lessons
- 408Red Teaming3 lessons
- 409Evaluation of Frontier Systems3 lessons
- 410Responsible Deployment3 lessons
- 411Regulation7 lessons
- 412International Policy3 lessons
- 413Military AI3 lessons
- 414Economic Impact and Labor Markets3 lessons
- 415Existential Risk4 lessons
- 416Open vs Closed Models4 lessons
- 501Transformers (Research)3 lessons
- 502Mixture of Experts3 lessons
- 503Reasoning Models3 lessons
- 504Inference Scaling and Test-Time Compute3 lessons
- 505Memory Architectures3 lessons
- 506Agentic Systems (Research)3 lessons
- 507Synthetic Data3 lessons
- 508Self-Improvement3 lessons
- 509World Models3 lessons
- 510AI for Science3 lessons
- 511Robotics and Embodied AI3 lessons
- 512Multimodal Foundation Models3 lessons
- 513Evaluation Benchmarks3 lessons
- 514The Research Practice4 lessons
- 601Product Design for AI3 lessons
- 602UX for AI4 lessons
- 603Human Feedback3 lessons
- 604Model Selection3 lessons
- 605Failure Modes in Product3 lessons
- 606Deployment3 lessons
- 607Metrics for AI Products3 lessons
- 608User Testing for AI3 lessons
- 609Iterative Improvement3 lessons
- 610Business Cases for AI Features3 lessons
- 701AI for Automation3 lessons
- 702AI for Sales3 lessons
- 703AI for Marketing3 lessons
- 704AI for Finance3 lessons
- 705AI for Operations3 lessons
- 706AI for HR3 lessons
- 707AI for Legal3 lessons
- 708AI in Healthcare (Operating)3 lessons
- 709AI in Education3 lessons
- 710AI for Research3 lessons
- 711AI in Manufacturing3 lessons
- 712AI in Government3 lessons
- 801Prompt Injection4 lessons
- 802Data Poisoning3 lessons
- 803Model Theft and Extraction3 lessons
- 804Jailbreaks3 lessons
- 805Security Testing for AI3 lessons
- 806AI Red Teaming3 lessons
- 807Secure Deployment3 lessons
- 808Adversarial Examples3 lessons
- 809Model Privacy3 lessons
- 901Model Economics3 lessons
- 902Pricing3 lessons
- 903Infrastructure and GPU Costs3 lessons
- 904Business Models for AI4 lessons
- 905Product Strategy for AI Companies3 lessons
- 906Fundraising3 lessons
- 907Go-to-Market for AI3 lessons
- 908Scaling an AI Company3 lessons
- 909Enterprise Sales for AI4 lessons
X
ProgramAI Laboratories
Fourteen required labs. Where the discipline becomes capability.
- L01Prompt Library1 lessons
- L02Model Bake-off1 lessons
- L03RAG System1 lessons
- L04Vector Database Deployment1 lessons
- L05AI Coding Assistant1 lessons
- L06Document Analysis Pipeline1 lessons
- L07Multi-Agent Workflow1 lessons
- L08Rubric-Based Evaluation1 lessons
- L09Fine-Tune a Small Model1 lessons
- L10Deploy an AI Application1 lessons
- L11Latency and Cost Monitoring1 lessons
- L12Red-Team Your Own System1 lessons
- L13A/B Evaluation1 lessons
- L14End-to-End AI Product1 lessons