- Level Foundation
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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 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. NO HANDS-ON. Rather than a 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.Auto Summary
Become a Machine Learning Rock Star with this comprehensive course offered by Coursera, designed for data science and AI enthusiasts. Guided by expert instructors, this foundational course dives into the end-to-end practice of machine learning, a field hailed by Harvard Business Review as pivotal. With flexible subscription options like Starter and Professional, this course is perfect for those looking to understand and apply cutting-edge machine learning techniques. Join now and transform your understanding of this revolutionary technology.