Courses, Generative AI

Short Course on Evaluating and Debugging Generative AI Models Using Weights and Biases by DeepLearning AI [Free; Python]: Join Now!

Apoorva

Sep 4, 2023
2 min read

0 Comments

Online applications are invited for the Short Course on Evaluating and Debugging Generative AI Models Using Weights and Biases by DeepLearning AI.

About DeepLearning AI

DeepLearning AI is an education technology company that is empowering the global workforce to build an AI-powered future through world-class education, hands-on training, and a collaborative community. DeepLearning AI has created high-quality AI programs on Coursera that have gained an extensive global following. By providing a platform for education and fostering a tight-knit community, DeepLearning AI has become the pathway for anyone looking to build an AI career.

About Weights & Biases

At Weights & Biases, our mission is to build the best tools for machine learning. Our co-founders built Figure Eight, and our tools are being used by cutting-edge machine learning teams including OpenAI, NVIDIA, and Co: here. We’re looking for passionate, driven people who love to learn and collaborate in an inclusive work environment.

Course Highlights

Content Courtesy

Learn to evaluate programs utilizing LLMs as well as generative image models using platform-independent tools.
Instrument a training notebook, and add tracking, versioning, and logging.
Implement monitoring and tracing of LLMs over time in complex interactions.

What you’ll learn in this course?

Machine learning and AI projects require managing diverse data sources, vast data volumes, model and parameter development, and conducting numerous test and evaluation experiments. Overseeing and tracking these aspects of a program can quickly become an overwhelming task.

This course will introduce you to Machine Learning Operations tools that manage this workload. You will learn to use the Weights & Biases platform which makes it easy to track your experiments, run and version your data, and collaborate with your team.

This course will teach you to:

Instrument a Jupyter notebook
Manage hyperparameter config
Log run metrics
Collect artefacts for dataset and model versioning
Log experiment results
Trace prompts and responses to LLMs over time in complex interactions

When you complete this course, you will have a systematic workflow at your disposal to boost your productivity and accelerate your journey toward breakthrough results.

Who should join?

Anyone who has familiarity with Python and PyTorch or similar frameworks and an interest in managing, versioning, and debugging their machine learning workflow.