AI Luminaries
A curated collection of videos featuring top experts in artificial intelligence.
Overview
Learn DSPy, a Pythonic framework for building robust AI systems without brittle prompts. Define tasks with signatures, compose modules, evaluate with metrics, and optimize prompts or models—all in an iterative, modular workflow.
What you'll learn
- Configure language models and create DSPy programs
- Define AI tasks using structured signatures
- Compose modules into multi-step AI workflows
- Prepare development data with Example objects
- Create metrics and evaluate output quality
- Optimize prompts and model weights using DSPy optimizers
- Save and load optimized programs for iterative improvement
Advantages and disadvantages
Advantages
- University courses you can audit for free, with lectures, readings and practice quizzes.
- A verified certificate from the university if you pay for it.
- Self-paced: start any time.
Disadvantages
- Graded assignments and the certificate need the paid track.
- Audit access can expire a few weeks after the course ends.
- Learning is free, but the certificate costs money.
- Some parts (graded work, certificate) are paid.
Some points apply to every course of this kind; see how we rank.
Free to audit
- Free: Choose "Audit this course" when you enrol: lectures, readings and practice are free.
- Paid: Graded assignments and the verified certificate (Certificate $45). Audit access may end after the course closes.
Before you start
Beginner: Prompt Engineering and Optimization (DSPy, Python)
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