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Eric Siegel

Eric Siegel

Current City: San Francisco, CA

Ph.D., Computer Science, Columbia University
M.S., Computer Science, Columbia University

Professional experience:
Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who makes machine learning understandable and captivating. He is the founder of the long-running Predictive Analytics World and the Deep Learning World conference series, which have served more than 17,000 attendees since 2009, the instructor of the end-to-end, business-oriented course "Machine Learning Leadership and Practice – End-to-End Mastery", a popular speaker who's been commissioned for more than 110 keynote addresses, and executive editor of The Machine Learning Times. He authored the bestselling "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die", which has been used in courses at more than 35 universities, and he won teaching awards when he was a professor at Columbia University, where he sang educational songs to his students. Eric also publishes op-eds on analytics and social justice.

Courses I teach include

Machine Learning Leadership and Practice – End-to-End Mastery

LinkedIn profile:

Twitter account:

Facebook profile:

Authored works:

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

Invited speaker at conferences:

Commissioned for more than 110 keynote addresses on machine learning and predictive analytics

What students are saying:

"This is increasingly essential knowledge for both business leaders who know that data must be tapped for competitive advantage and analytics professionals who need to understand how to help businesses tap that power. Each party needs to know a bit more - not too much, but enough - about the other's world to be effective together and deliver results. Finding that balance of how much tech and data and how much business outcome to put into a course is really difficult and I have not seen anyone strike that balance like Prof. Siegel. In addition to this unique capability, Prof. Siegel brings relevant and relatable cases, actual hands-on work in an approachable format, and a keen sense of humor as he lets geek flag fly high. Take this course."

— Drew Smith, VP - Analytics Leadership Consortium, International Institute for Analytics

"An exceptionally insightful and unique course by none other than the maestro of predictive analysis Dr. Eric Siegel. It elucidates us how launching machine learning – aka predictive analytics – improves marketing, financial services, fraud detection, and many other business operations. I thank SAS for collaborating with Eric for this amazing initiative."

— Ajith Nair, Graduate of Fr. Conceicao Rodrigues Institute of Technology

"If you have any interest in machine learning from a technical or even a business/management position, take this course by Eric Siegel, the guy who wrote the book on predictive analytics."

— Jason Green, Data Engineer, Proofpoint

"Excellent and very well done. Engaging throughout, with excellent references and supplemental videos and articles. Relevant concepts and terms introduced and well-motivated. The last section of the course was superb — the coverage of ethical issues and the discussion of the common/familiar objections and misunderstandings about AI is something that everyone should hear/watch. For many learners, that’s more important than knowing technical details."

— Philip Nyman, Principal Training Specialist, MCT Analytics, University of Illinois at Urbana-Champaign

"I’m so glad you put this together [course 1]. This specialization fulfills an unmet need. I really liked these aspects in the videos: the definitions, which made it easy to understand concepts; the quotes, which emphasized the key points; and the visuals, which kept me engaged. I also have to say this course was very entertaining. Good teachers reinforce concepts through stories, and the instructor did a great job of that. Coming into the course, I expected to like the ethics discussion the most, and while that didn’t disappoint, two other sections were superb and turned out to be the two most useful parts of this course: 1) the discussion about data cleansing and 2) misjudging/miscommunicating predictive performance. These important concepts were explained clearly with easy to understand examples. So come with an open mind. This course is very different from the typical technical course on machine learning — be prepared to learn something new and very important."

— Phil Bangayan, Principal Data Scientist, Teradata