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This edX course is for people who find maths intimidating but need it for AI. Rather than aiming to turn learners into mathematicians, it introduces the essential ideas and their notation across calculus, linear algebra, probability, statistics and optimisation. Python serves as the working tool, so concepts are tried out on real data.
Readers who studied maths long ago and want a refresher in the context of machine learning will find the framing useful. The intermediate level label indicates it builds on some earlier familiarity with the subject.
Want to study machine learning or artificial intelligence, but worried that your math skills may not be up to it? Do words like “algebra”and “calculus” fill you with dread? Has it been so long since you studied math at school that you’ve forgotten much of what you learned in the first place?
You’re not alone. Machine learning and AI are built on mathematical principles like Calculus, Linear Algebra, Probability, Statistics, and Optimization; and many would-be AI practitioners find this daunting. This course is not designed to make you a mathematician. Rather, it aims to help you learn some essential foundational concepts and the notation used to express them. By leveraging the power of Python, the course provides a hands-on approach to working with data and applying the techniques you’ve learned.
This course includes content authored by Microsoft Corporation. Copyright 2020-2023 Microsoft Corporation. All Rights Reserved.
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