The course introduces DSPy—its installation, programming, evaluation, and optimization for building AI systems. It covers using LMs, designing signatures, and composing modules for advanced tasks.
Overview
Syllabus
- Unit 1: Introduction to DSPy
- Installing DSPy for Language Models
- DSPy Framework Introduction Quiz
- Unit 2: Using Language Models in DSPy
- Basic LM Operations and History
- Switching Models with Context Managers
- Structured Messages and History Exploration
- Customizing LM Parameters for Creative Output
- Unit 3: Creating Your Own Signature in DSPy
- Your First Sentiment Classifier Signature
- Creating Your First Summarization Signature
- Building a Multi-Input Question Answering Signature
- Creating Emotion Classifiers with Class Signatures
- Building a Fact Checking Signature
- Unit 4: Modules: The DSPy Building Blocks
- Building Your Second Sentiment Classifier
- Step by Step Math Reasoning
- Code Powered Candy Distribution
- Tools and Reasoning with ReAct
- Comparing Paths for Better Answers