Foundations of DSPy: Prompt Engineering & Optimization

Why should you attend?

This comprehensive training program introduces learners to the fundamentals of prompt engineering and optimization using DSPy, a powerful framework for building and optimizing language model applications. The course begins with essential concepts of prompt engineering, exploring what prompts are, why they matter for large language models, and the differences between manual and automated prompting approaches. Participants will gain hands-on experience with DSPy installation, setup, and core programming concepts including signatures, modules, and pipelines. Through practical exercises, learners will build their first DSPy project, creating simple AI tasks like question-and-answer bots while mastering the step-by-step workflow development process. The program progresses to advanced topics including dataset integration, multi-step pipeline construction, and real-world applications such as document extraction and retrieval-augmented generation integration. Learners will explore DSPy optimization techniques, comparing different optimizers and tuning parameters for improved accuracy and efficiency. The course emphasizes practical debugging and testing methodologies, ensuring participants can identify and resolve prompt-related issues effectively. Culminating in collaborative mini-projects and a comprehensive capstone experience, participants will demonstrate their mastery by building, presenting, and refining AI tools using DSPy principles and best practices.