About this Specialization

200,674 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
50%
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

Approx. 4 months to complete

Suggested 4 hours/week

English

Subtitles: English, Greek, Spanish
Learner Career Outcomes
50%
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

Approx. 4 months to complete

Suggested 4 hours/week

English

Subtitles: English, Greek, Spanish

There are 3 Courses in this Specialization

Course1

Course 1

Mathematics for Machine Learning: Linear Algebra

4.7
stars
6,199 ratings
1,185 reviews
Course2

Course 2

Mathematics for Machine Learning: Multivariate Calculus

4.7
stars
3,100 ratings
522 reviews
Course3

Course 3

Mathematics for Machine Learning: PCA

4.0
stars
1,648 ratings
372 reviews

Offered by

Imperial College London logo

Imperial College London

Frequently Asked Questions

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • 3/4 hours a week for 3 to 4 months

  • High school maths knowledge is required. Basic knowledge of Python can come in handy, but it is not necessary for courses 1 and 2. For course 3 (intermediate difficulty) you will need basic Python and numpy knowledge to get through the assignments.

  • We recommend taking the courses in the order in which they are displayed on the main page of the Specialization.

  • This is a non-credit Specialization.

  • 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.

More questions? Visit the Learner Help Center.