IBM Masterclass & Hackathon: AI Explainability

The IBM AI Explainability Masterclass and Hackathon is for all data scientists, AI developers, ML engineers, and curious computer science students looking to take their skills further and add explainability to their data models. 

Explainability is the ability for data scientists to produce applicable results for their peers, managers, and end users. Can your results be understood and applied by other data scientists and stakeholders? It is up to you as a data scientist to use your business knowledge, mathematical, and programmatic skills to communicate your findings and methods. Explainability is an important tool used to make your reasoning behind each decision transparent and repeatable.

In this course, learn the importance of building an explainability workflow and how to implement these practices from the beginning. Then, using your new skills and tools, apply what you have learned by submitting your own project to the hackathon for a chance at cash prizes.