Description
Rehbar AI provides a comprehensive 5-day course designed for beginners interested in applied AI. The course covers essential concepts such as Large Language Models (LLMs), embeddings, vector search, Retrieval-Augmented Generation (RAG), and GraphRAG. Participants will engage in hands-on practice using an open-source application, which they can run locally on their machines. The course is structured into 12 short chapters, requiring about 2 hours of study per day.
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The course is entirely free, with no prior knowledge of mathematics or machine learning required. It is ideal for beginners who are comfortable using a terminal and have basic Python skills. By the end of the course, participants will have built their own GraphRAG application, gaining a clear understanding of how an LLM can transform search results into coherent answers.
Rehbar AI emphasizes practical learning, allowing participants to create a knowledge graph and use it to answer questions. The course also provides a certificate of completion, which can be downloaded as a PDF and shared on LinkedIn. The practice app is open source and runs locally using Docker, ensuring accessibility without additional costs.
Overall, Rehbar AI's course equips learners with the skills to integrate AI models into products, a valuable capability in today's tech-driven world. The focus on GraphRAG highlights the importance of understanding relationships between data points, setting participants apart in the field of AI.
- CategoryCorporate Training & E-Learning
- Pricing ModelFree
- DeploymentRuns locally
- PlatformsWeb
Rehbar AI's Core Features
Free 5-day course
Covers LLMs, RAG, GraphRAG
Open-source practice app
Certificate of completion
No prior AI knowledge needed
Hands-on learning approach
GraphRAG application building
Local deployment with Docker
How to use Rehbar AI?
Meet LLMs: Introduction to LLMs
Talk to an LLM: Coding interactions
Text as numbers: Understanding embeddings
Retrieval: Implementing vector search
GraphRAG: Building and using GraphRAG
Rehbar AI's Use Cases
- AI Learning
- Skill Development
- Open Source Practice
- Certificate Achievement
- GraphRAG Application
