Evaluating and Debugging Generative AI

About this course

Generative AI models are powerful, but they're also unpredictable. This course teaches you how to systematically track experiments, monitor what your models are doing, and debug when things go wrong. Created by DeepLearning.AI, a trusted authority in AI education, this hands-on course focuses on practical tools and workflows that separate confident AI practitioners from those flying blind.

What you'll learn

• Set up experiment tracking to compare GenAI model versions and configurations side-by-side
• Monitor inputs and outputs in real time to catch unexpected behavior early
• Use Weights & Biases (W&B) for logging, versioning, and analyzing model performance
• Debug common failure modes in generative models—hallucinations, inconsistent outputs, and more
• Build reproducible workflows so your experiments aren't lost or forgotten
• Interpret logs and metrics to make data-driven decisions about model improvements
• Apply these techniques to your own GenAI projects, whether LLMs, image generation, or other tasks

Who this is for

If you're building or working with generative AI—whether in a startup, an established tech company, or your own projects—you need to know how to evaluate and fix what's going wrong. This course is for anyone serious about moving past experimentation and into reliable, professional AI workflows.

• AI engineers and developers — master the debugging and monitoring tools that separate hobbyist projects from production systems
• Data scientists and ML researchers — streamline your experiment tracking so you can focus on innovation instead of spreadsheets

Prerequisites

Familiarity with Python and basic machine learning concepts is helpful. You should feel comfortable running code and reading JSON or YAML files. No deep theoretical ML background is required—this course is practical, not mathematical.

Why this matters for Indian learners

India's AI talent pool is growing fast, and companies across Bangalore, Hyderabad, and Delhi are actively hiring AI engineers. The ability to debug and evaluate GenAI systems is a rare, high-value skill that sets you apart in competitive hiring. Whether you're joining Infosys, TCS, startups like Unacademy or Freshworks, or building your own AI product, knowing how to monitor and improve your models directly impacts your project's success and your career trajectory.

Frequently asked questions

Is this course really free?

Yes. This course is completely free—no hidden fees, no paid upgrades required to learn the core material.

How long will it take to complete?

The course runs about 1 hour. You can finish it in one sitting or spread it across a week, working through one lesson per day at a relaxed pace.

Will I get a certificate?

This course does not offer a formal certificate. However, the skills you gain—experiment tracking, debugging, and model monitoring—are immediately useful on your real projects and resume.