About this Specialization

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Behind numerous standard models and constructions in Data Science there is mathematics that makes things work. It is important to understand it to be successful in Data Science. In this specialisation we will cover wide range of mathematical tools and see how they arise in Data Science. We will cover such crucial fields as Discrete Mathematics, Calculus, Linear Algebra and Probability. To make your experience more practical we accompany mathematics with examples and problems arising in Data Science and show how to solve them in Python.
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. 6 months to complete
Suggested 4 hours/week
English
Subtitles: English
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. 6 months to complete
Suggested 4 hours/week
English
Subtitles: English

There are 4 Courses in this Specialization

Course1

Course 1

Discrete Math and Analyzing Social Graphs

4.5
stars
232 ratings
55 reviews
Course2

Course 2

Calculus and Optimization for Machine Learning

3.9
stars
76 ratings
23 reviews
Course3

Course 3

First Steps in Linear Algebra for Machine Learning

4.2
stars
49 ratings
8 reviews
Course4

Course 4

Probability Theory, Statistics and Exploratory Data Analysis

4.7
stars
120 ratings
28 reviews

Offered by

National Research University Higher School of Economics logo

National Research University Higher School of Economics

Start working towards your Master's degree

This specialization is part of the 100% online Master of Data Science from National Research University Higher School of Economics. If you are admitted to the full program, your courses count towards your degree learning.

Frequently Asked Questions

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  • 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.

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 6-8 months.

  • As prerequisites we assume precollege level math, basic programming in python (functions, loops, recursion) and common sense. Our intended audience are all people that work or plan to work in Data Science.

  • We recommend taking the courses in the order presented, as each subsequent course uses some knowledge from previous courses.

  • Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. In the case of this particular Specialization the credit will be accepted by this masters program: https://www.coursera.org/degrees/master-of-data-science-hse

  • You will be able to understand mathematics behind Data Science. This will boost your skills in Data Analysis.

More questions? Visit the Learner Help Center.