Mastering Large Language Models with the Cohere API
42mIntermediate2024-12-04
Authors
Nayan Saxena
Course details
The AI world keeps shifting, as developers and data scientists figure out new and better ways to create large language models (LLMs) that answer requests efficiently and effectively. Cohere gives developers access to a powerful suite of LLMs and three models–Command, Rerank, and Embed–that will let you build powerful search, summary, and conversational systems. In this course, learn about the Cohere API, and how to integrate it with retrieval-augmented generation approaches that allow you to build powerful AI applications.
Skills covered
APIsNatural Language Processing (NLP)Introduction toArtificial Intelligence (AI)Software Development
Concepts
0. Introduction
- 01 - The power of Cohere
- 02 - What you should know
- 03 - Exercise files and setting up your environment
1. Introduction to Large Language Models and Cohere
- 04 - What are large language models
- 05 - Overview of the Cohere platform
- 06 - Cohere s foundational models - Command, Rerank, and Embed
2. Advanced Text Generation Techniques
- 07 - Introduction to the Cohere Chat API
- 08 - Generating simple responses with streaming
- 09 - Managing multi-message conversations and tool use
3. Building Conversational Agents and RAG Systems
- 10 - Retrieval-augmented generation (RAG) overview
- 11 - Designing RAG applications with the Command and Chat APIs
- 12 - Connectors and external data for grounded conversations
4. Semantic Search and Classification
- 13 - Semantic search and classification overview
- 14 - Dense retrieval and reranking
- 15 - Building applications with query and rerank endpoints
Conclusion
- 16 - Next steps in building LLM applications