Mathematics for Machine Learning Specialization

Mathematics for Machine Learning. Learn about the prerequisite mathematics for applications in data science and machine learning

123,477 already enrolled
Instructor(s): David Dye +3 more
Image of instructor, David DyeImage of instructor, Samuel J. CooperImage of instructor, A. Freddie Page

Subtitles: English, Arabic,

Offered By

Imperial College London

About this Specialization

75,693 recent views
For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science. This specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science. In the first course on Linear Algebra we look at what linear algebra is and how it relates to data. Then we look through what vectors and matrices are and how to work with them. The second course, Multivariate Calculus, builds on this to look at how to optimize fitting functions to get good fits to data. It starts from introductory calculus and then uses the matrices and vectors from the first course to look at data fitting. The third course, Dimensionality Reduction with Principal Component Analysis, uses the mathematics from the first two courses to compress high-dimensional data. This course is of intermediate difficulty and will require Python and numpy knowledge. At the end of this specialization you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning.
Learner Career Outcomes
47%
Started a new career after completing this specialization.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Approximately 4 months to complete
Suggested pace of 4 hours/week
English
Learner Career Outcomes
47%
Started a new career after completing this specialization.
Shareable Certificate
Earn a Certificate upon completion
100% online courses
Start instantly and learn at your own schedule.
Flexible Schedule
Set and maintain flexible deadlines.
Beginner Level
Approximately 4 months to complete
Suggested pace of 4 hours/week
English

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

There are 3 Courses in this Specialization

Course1

Course 1

Mathematics for Machine Learning: Linear Algebra

4.7
stars
9,717 ratings
1,953 reviews
Course2

Course 2

Mathematics for Machine Learning: Multivariate Calculus

4.7
stars
4,695 ratings
832 reviews
Course3

Course 3

Mathematics for Machine Learning: PCA

4.0
stars
2,582 ratings
643 reviews

Offered by

Placeholder

Imperial College London

Frequently Asked Questions

More questions? Visit the Learner Help Center.