GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
RAG Time is tailored for those looking to systematically learn and apply Retrieval-Augmented Generation techniques in a structured 5-week program.
Good fit when
- When you need a detailed, week-by-week learning path specifically focused on the nuances of RAG techniques, from basics to advanced applications.
- If your project requires understanding both indexing methods (like HNSW and Hybrid Search) and generation models for effective RAG implementations.
Avoid when
- If you prefer ad-hoc or self-directed learning without a structured timeline. Other tools may offer more flexible formats, which can be preferable if adhering to strict schedules is not ideal.
- When your focus is solely on either indexing or generation models and not the integration of both for RAG. In this case, specialized resources for just indexing or model training might suffice.
- Requirements:
- Min 8 GB RAM
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (459d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Backing
Company context for Microsoft. Display-only - separate from trust and ranking.
- Company
- Microsoft·GitHub org profile·Jul 11, 2026
- Employees
- 221,000·Wikidata (P1128 employees)·Jul 11, 2026
- Commercial model
- Pure OSS·GitHub org profile (public repos)·Jul 11, 2026
Install
git clone https://github.com/microsoft/rag-timeSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides a structured learning path and resources for mastering Retrieval-Augmented Generation (RAG) techniques.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Sep 20, 2026
Categories
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README
RAG Time: Ultimate Guide to Mastering RAG 🚀 Master RAG with RAG Time! Learn how to build smarter AI applications with Retrieval Augmented Generation. This repo includes step by step guides, live coding samples, and expert insights—everything you need to go from beginner to RAG p...
For agents
This page has a .md twin and JSON over the API.