Free course with 4 live sessions

AI Quality Workshop

Driving ML Performance
and Trustworthiness

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Register below for class starting Aug. 25

For class starting Oct. 13, go here.


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Hands-on strategies for data scientists. Taught by leading experts.

Are you a data scientist interested in learning more about how to analyze and improve the performance and trustworthiness of your machine learning models? This 4-session live course is for you. AI Quality: Driving ML Performance and Trustworthiness is a free course for practitioners, taught live by experts from leading universities. Each 2-hour class covers the essentials of a key topic for managing machine learning models.

Aug. 25-Sept. 15
4 consecutive Thursdays


New! US, EMEA and India convenient time


8:00 AM Pacific
11:00 AM Eastern
4:00 PM London
8:30 PM Delhi


For data science professionals
In corporate, government, or university settings.

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In this free course, you will learn:

  • ML Explainability  - How do you explain model predictions? What are best practices for local and global explanations, and conceptual soundness assessment? Which methods are most appropriate for various use cases?
  • Accuracy and Performance Debugging - How can you systematically analyze model accuracy? How can you rapidly identify model errors  to drive improvements? 
  • Model Drift - Does your production model need to be refreshed? How do you measure model score and data drift on an ongoing basis? How can you understand the root causes of drift, and debug your models in a directed way? 
  • Fairness  - How can you ensure that your models are set up to be fair and compliant, and remain fair over time? What are best practices for choosing fairness metrics, understanding root causes and mitigating fairness gaps, leveraging humans in the loop?
  • NLP Model Quality - What are the specific challenges of NLP model quality? What are best practices for explainability, debugging and improving the performance of NLP models?
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What you get:

  • Free 4-week course taught live by leading experts in AI Quality and machine learning effectiveness 
  • Free use of Veritable software for the duration of the course
  • A class filled with peers tackling real-world projects, and access to the AI Quality Slack community
  • Course certificate, upon completion of all 4 classes

Register here for the course starting Aug. 25

This course is limited to AI and ML practitioners in corporate, government and university settings. Please use your corporate, government or university email address to apply and we will inform you if you are selected to participate. Submit your application soon - spots are limited!

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Anupam_Datta 1

Anupam Datta


Carnegie Mellon University

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Arridhana Ciptadi


Georgia Institute of Technology


Divya Gopinath




Piotr Mardziel


University of Maryland

Shayak_Sen 1

Shayak Sen


Carnegie Mellon University

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About Veritable

Veritable provides AI Quality solutions that analyze machine learning, drive model quality improvements, and build trust. Powered by enterprise-class Artificial Intelligence (AI) Explainability technology based on six years of research at Carnegie Mellon University, Veritable’s suite of solutions provides much-needed model transparency and analytics that drive high model quality and overall acceptance, address unfair bias, and ensure governance and compliance.

Learn More