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ONLINE: Machine Learning Leadership and Practice: End-to-End Mastery

Take this online course anytime – or to ramp up before the conference…

… if you’re new to ML and predictive analytics

… or if you’re a data scientist pursuing the business side of ML

… or if you’re a data scientist pursuing special advanced topics


Course Description

While there are many how-to courses for hands-on techies, there are practically none that also serve the business leadership of machine learning – a striking omission, since success with machine learning relies on a very particular project leadership practice just as much as it relies on adept number crunching.

By filling that gap, this course empowers you to generate value with ML. It delivers the end-to-end expertise you need, covering both the core technology and the business-side practice.

Why cover both sides? Because both sides need to learn both sides! This includes everyone leading or participating in the deployment of ML.

Accessible to business-level learners and yet vital to techies as well, this course will guide you to lead and launch machine learning.

This course also serves as prep for Machine Learning Week’s advanced, in-person workshops.



Learning Objectives

After taking Machine Learning Leadership and Practice: End-to-End Mastery, you will be able to:

Lead ML: Manage or participate in the end-to-end implementation of machine learning

Apply ML: Identify the opportunities where machine learning can improve marketing, sales, financial credit scoring, insurance, fraud detection, and much more

Greenlight ML: Forecast the effectiveness of and scope the requirements for a machine learning project and then internally sell it to gain buy-in

Regulate ML: Manage ethical pitfalls, the risks to social justice that stem from machine learning – aka ethical AI



Eric Siegel, Ph.D., is a leading consultant and former Columbia University professor who helps companies deploy machine learning. He is the founder of the long-running Machine Learning Week conference series and its new sister, Generative AI Applications Summit, the instructor of the acclaimed online course “Machine Learning Leadership and Practice – End-to-End Mastery,” executive editor of The Machine Learning Times, and a frequent keynote speaker. He wrote the bestselling Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which has been used in courses at hundreds of universities, as well as The AI Playbook: Mastering the Rare Art of Machine Learning Deployment. Eric’s interdisciplinary work bridges the stubborn technology/business gap. At Columbia, he won the Distinguished Faculty award when teaching the graduate computer science courses in ML and AI. Later, he served as a business school professor at UVA Darden. Eric also publishes op-eds on analytics and social justice.

Eric has appeared on Bloomberg TV and Radio, BNN (Canada), Israel National Radio, National Geographic Breakthrough, NPR Marketplace, Radio National (Australia), and TheStreet. Eric and his books have been featured in Big Think, Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, Fast Company, The Financial Times, Forbes, Fortune, GQ, Harvard Business Review, The Huffington Post, The Los Angeles Times, Luckbox Magazine, MIT Sloan Management Review, The New York Review of Books, The New York Times, Newsweek, Quartz, Salon, The San Francisco Chronicle, Scientific American, The Seattle Post-Intelligencer, Trailblazers with Walter Isaacson, The Wall Street Journal, The Washington Post, and WSJ MarketWatch.

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