Plan de estudios

Solo títulos de módulos y lecciones. El contenido completo se desbloquea tras la inscripción.

1. Module M01

   1. Lesson M01-L01 — What RAG Really Is (Not Chat-with-PDF)
   2. Lesson M01-L02 — Layered Production RAG Architecture
   3. Lesson M01-L03 — Where RAG Fits in Complete AI Systems
   4. Lesson M01-L04 — Corpus Rights, Privacy & Knowledge Product Framing

2. Module M02

   1. Lesson M02-L01 — Document Parsing Pipelines
   2. Lesson M02-L02 — Chunking Strategies, Overlap & Inspection
   3. Lesson M02-L03 — Embeddings via Provider-Neutral Interfaces
   4. Lesson M02-L04 — Knowledge Stores & Metadata Design

3. Module M03

   1. Lesson M03-L01 — Retrieval Strategies (Top-k, Thresholds, Multi-Doc)
   2. Lesson M03-L02 — Context Construction & Prompt Augmentation
   3. Lesson M03-L03 — Answer Generation, Citations & Source Attribution
   4. Lesson M03-L04 — Hallucination Reduction & Weak-Context Refusal

4. Module M04

   1. Lesson M04-L01 — Evaluation Fundamentals (Golden Sets & Faithfulness)
   2. Lesson M04-L02 — Knowledge Lifecycle & Updating Indexed Content
   3. Lesson M04-L03 — Multi-Document Systems & Knowledge Workspace Patterns
   4. Lesson M04-L04 — Ship JP-JA15 Production-Ready RAG Platform