Course Description
This course provides comprehensive training on utilizing Mistral AI’s suite of both open source and commercial models through web interfaces and API integrations. Participants will learn how to effectively operate models ranging from Mistral 7B to the sophisticated Mixtral 8x22B, utilize JSON formatted responses for better software integration, and enhance LLM’s capabilities with user-defined functions via API calls.
What Students Will Learn
Students will gain hands-on experience with Mistral AI’s varied models, understand the applications of JSON mode in LLM responses, and implement advanced features like Retrieval Augmented Generation (RAG). Key learning outcomes include:
- Choosing the appropriate Mistral model based on task complexity and performance needs.
- Executing API calls to interact with Mistral models and performing tasks ranging from basic classification to complex coding challenges.
- Utilizing Mistral’s function calling capability to perform database queries and other code-dependent tasks.
- Designing and implementing a basic RAG system to enhance chat capabilities with data retrieval and processing.
- Developing a chat interface to query and interact with uploaded documents using Mistral models.
Prerequisites
This course is designed for beginners but having prior knowledge in the following areas will help:
- Basic understanding of AI and machine learning concepts.
- Familiarity with JSON format and API usage.
- Experience in Python programming is beneficial especially for understanding function calling and API interactions.
Course Coverage
- Understanding and accessing Mistral’s range of LLM models.
- Effective use of JSON mode for structuring LLM responses.
- API integrations for calling user-defined Python functions.
- Building and applying Retrieval Augmented Generation systems.
- Creating interactive chat interfaces with Mistral models.
Who This Course is For
This beginner-friendly course is ideal for anyone interested in mastering the advanced functionalities of Mistral AI's LLMs, especially those previously exposed to basic prompt engineering or AI model manipulation courses.
Application of Skills
Upon completing this course, learners can apply these skills in various real-world scenarios such as:
- Enhancing enterprise software systems with powerful, integrated AI capabilities.
- Developing advanced AI-driven applications for data analysis, content generation, or customer interaction.
- Improving system automation by incorporating intelligent query handling and information retrieval features.
Instructor
Sophia Yang
Instructor