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An End-to-End Guide to Leading and Launching ML. This expansive machine learning curriculum is accessible to business-level learners and yet …

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An End-to-End Guide to Leading and Launching ML. This expansive machine learning curriculum is accessible to business-level learners and yet vital to techies as well. It covers both the state-of-the-art techniques and the business-side best practices.

About this Specialization

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Machine learning reinvents industries and runs the world. Harvard Business Review calls it “the most important general-purpose technology of our era.” But while there are so many how-to courses for hands-on techies, there are practically none that also serve the business leaders 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. NO HANDS-ON. Rather than hands-on training, this specialization serves both business leaders and burgeoning data scientists with expansive, holistic coverage. BUT TECHNICAL LEARNERS SHOULD TAKE ANOTHER LOOK. Before jumping straight into the hands-on, as quants are inclined to do, consider one thing: This curriculum provides complementary know-how that all great techies also need to master. WHAT YOU'LL LEARN. How ML works, how to report on its ROI and predictive performance, best practices to lead an ML project, technical tips and tricks, how to avoid the major pitfalls, whether true AI is coming or is just a myth, and the risks to social justice that stem from ML.

Course Currilcum

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