Modern AI Foundations
Course Overview
A structured, no-math journey from "what is AI?" to building, evaluating, and engineering real-world AI systems. Learners progress through 20 carefully sequenced modules covering models, tokens, context windows, prompt engineering, context engineering, RAG, AI agents, harnesses, coding agents, MCP, multi-agent systems, evaluation, production engineering, and the future trajectory of AI. No prerequisites beyond basic digital literacy — designed for complete beginners who want to understand and build with modern AI.
What You'll Learn
Learning Outcomes
Explain what AI is and how it differs from traditional software
Understand core architecture of modern AI systems
Build functional AI applications
Evaluate AI system quality systematically
Design, deploy, and operate reliable AI systems
Critically assess AI capabilities and limitations
Syllabus Overview
Modern AI Foundations is a comprehensive, beginner-friendly course that takes learners from absolute zero to building real-world AI systems. Across 20 modules and 10 weeks, students explore what AI actually is, how models work, the art of prompt and context engineering, retrieval-augmented generation, AI agents, multi-agent systems, evaluation, and production engineering. No math, no programming prerequisites — just clear explanations, interactive exercises, and practical knowledge.
Course Structure
Modules & Lessons
20 modules · 20 lessons
Module 1 defines AI as software that learns patterns from data, contrasting it with traditional rule-based software, and explores narrow vs general AI, why AI feels sudden, and what it can and cannot do.
- 01What AI Actually Is0
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This Course
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