Masterclass: AI Explainability
Go beyond the code, advance towards responsible and trustworthy AI

IBM EXPLAINABILITY MASTERCLASS & HACKATHON

ACCESS THIS MASTERCLASS FOR FREE
AUSTIN EOVITO
AI Explainability Expert

IBM EXPLAINABILITY MASTERCLASS IS LIVE!

WATCH THE FREE COURSE AND APPLY YOUR SKILLS in THE ONLINE HACK

March 17 - May 1
ONLINE
ACCESS THE FREE MASTERCLASS

MASTERCLASS

Quickly learn new data science concepts with this free 90-minute micro-course.

HACKATHON

Create your own project to showcase to win from the $8,000 prize pool and an IBM skill badge.

MENTORSHIP

Connect 1:1 with IBM data science experts for help and guidance on your project.

IBM skills Badge

Complete your journey by submitting your work for an IBM Explainability Skills Badge*. To apply, just prove that:

You have Completed the IBM Explainability Masterclass course.

You have passed the in-course quizzes and the end-of-course comprehensive assessment.

You successfully participated in the online hackathon which includes acceptance and approval of your project submission by the judges.

Badges will be issued up to 2 weeks after the final submission deadline date. For questions related to your badge, email eovito@ibm.com.

*NOTICE: IBM leverages the services of Credly's Acclaim platform, a 3rd party data processor authorized by IBM and located in the United States, to assist in the administration of the IBM Digital Badge program. In order to issue you an IBM Digital Badge, your personal information (name, email address, and badge earned) will be shared with the Credly’s Acclaim platform.  You will receive an email notification from Acclaim with instructions for claiming the badge. Your personal information is used to issue your badge and for program reporting and operational purposes. It will be handled in a manner consistent with IBM privacy practices.  The IBM Privacy Statement can be viewed here:  https://www.ibm.com/privacy/us/en/.   IBM employees can view the IBM Internal Privacy Statement here:  https://w3.ibm.com/w3publisher/w3-privacy-notice.
PRESENTATION

What will you LEARN?

New open-source and IBM data science tools like AIX360 and Lale

How to explain your model to any stakeholder

How to integrate explainable workflows

Who is this for?
Data Scientists, AI Developers, ML Engineers
Enterprises, Startups, Government Agencies, NGOs
Students and Life-long Learners

Why explainability?

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.  Each submission for the hackathon will have a chance at cash prizes during the 6-week competition. 

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