Course covers topics relevant to model explainability, accuracy, and fairness; is relevant to EU AI law and other industry guidelines

TruEra, a global provider of AI Quality solutions, has announced the launch of its first free course for data science practitioners. The live, online course ‘AI Quality: Driving ML Performance and Trustworthiness,’ will run over four consecutive weeks from October 27 to November 17, 2021. It will be led by esteemed Artificial Intelligence (AI) and machine learning (ML) academic Anupam Datta, Professor of Electrical and Computer Engineering and (by courtesy) Computer Science at Carnegie Mellon University. Datta is also Co-Founder, President, and Chief Scientist at TruEra, and will be supported on the course by AI experts and practitioners on his research team who hold degrees from Carnegie Mellon University, Georgia Institute of Technology, MIT and the University of Maryland. In their current roles at TruEra, this team works with major enterprises and data science teams around the world to improve their success with AI and ML.

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During the course, data scientist practitioners from corporate or government settings will learn how to analyze and improve the performance and trustworthiness of their machine learning models. The course covers critical, timely topics such as AI explainability, model accuracy, drift and stability, and fairness/model bias.

“Around the world, there is a growing regulatory focus and consensus regarding the need for transparent, understandable, and well-performing AI. AI Quality is essential for firms to make the most of machine learning, achieving operational goals while building trust with customers and external stakeholders,” said Datta. “We are excited to share our expertise with data science practitioners from business, government, and nonprofit institutions, with a view to helping them analyse and improve the performance and trustworthiness of their machine learning models.”

A certificate will be issued upon completion to prove participation in the course and proficiency in the understanding of AI Quality.

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