Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

Luis Serrano

Luis Serrano

Instructor DeepLearning.AI




AI scientist, popular YouTuber, and author of Grokking Machine Learning. I am a quantum AI research scientist at Zapata Computing in Toronto, Canada, developing machine learning algorithms to work in quantum computers. Before that, I lived in Silicon Valley, where I worked at the following companies: Apple: I was a lead AI educator, in charge of teaching machine learning to the employees and doing internal consulting in AI related projects. Udacity: I was the head of content for AI and Data Science, managing the team that created online courses in AI, ML, Deep Learning, Data Science, etc. Google: I was part of the video recommendations team at YouTube, where we trained machine learning algorithms to recommend videos in the main page. Before my life in technology, I was a research mathematician. I did a Bachelors and Masters at the University of Waterloo, a PhD at the University of Michigan, and an NSERC Postdoctoral Fellowship at the Université du Québec à Montréal. My love for math goes way back. As a high school student, I participated in the International Mathematical Olympiads, representing my native country of Colombia in the IMO 98 and IMO 99.
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About this Specialization

Mathematics for Machine Learning and Data Science is a foundational online program created by DeepLearning.AI and taught by Luis Serrano. This beginner-friendly program is where you’ll master the fundamental mathematics toolkit of machine learning.

Many machine learning engineers and data scientists struggle with mathematics. Challenging interview questions often hold people back from leveling up in their careers, and even experienced practitioners can feel held by a lack of math skills. 

This specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use easy-to-follow plugins and visualizations to help you see how the math behind machine learning actually works. Upon completion, you’ll understand the mathematics behind all the most common algorithms and data analysis techniques — plus the know-how to incorporate them into your machine learning career.

Mathematics for Machine Learning and Data Science Specialization currently has Courses 1 and 2 available for enrollment, with Course 3 coming soon!

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