This course teaches you how to turn Anki and modern AI tools into an end‑to‑end intelligent learning system. You’ll start by mastering evidence‑based spaced‑repetition settings and high‑yield card design, then learn to use large language models to generate high‑quality cloze deletion flashcards from textbooks, lectures, research papers, videos, and transcripts. From there, you’ll build a practical automation pipeline with Python and the OpenAI API that ingests documents, generates cards in bulk, validates format and quality, and feeds import‑ready decks or directly updates your Anki collection. You’ll optimize mobile review using AnkiDroid and game‑controller workflows to convert commutes, walks, gym time, and short breaks into hundreds of low‑friction daily reviews. Finally, you’ll extend your setup with retrieval‑augmented generation, embeddings, and knowledge graphs (via platforms like AnythingLLM) so your system can detect gaps, avoid duplicates, map conceptual relationships, and surface the highest‑value next cards. By the end of the course, you’ll have a scalable, largely automated learning infrastructure that continually transforms your study materials into precise, personalized spaced‑repetition decks.