About this Specialization

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100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Beginner Level

Approx. 2 months to complete

Suggested 15 hours/week

English

Subtitles: English

Skills you will gain

CalculusProbabilityDiscrete MathematicsLinear Algebra

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Beginner Level

Approx. 2 months to complete

Suggested 15 hours/week

English

Subtitles: 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.

how it works

There are 4 Courses in this Specialization

Course1

Course 1

Discrete Math and Analyzing Social Graphs

4.2
stars
22 ratings
5 reviews
Course2

Course 2

Calculus and Optimization for Machine Learning

Course3

Course 3

First Steps in Linear Algebra for Machine Learning

Course4

Course 4

Probability Theory, Statistics and Exploratory Data Analysis

Instructors

Image of instructor, Vsevolod L. Chernyshev

Vsevolod L. Chernyshev 

Associate Professor
Faculty of Computer Science
Image of instructor, Dmitri Piontkovski

Dmitri Piontkovski 

Professor
Faculty of Economic Sciences
Image of instructor, Anton Savostianov

Anton Savostianov 

Lecturer
Faculty of Computer Science
Image of instructor, Ilya V. Schurov

Ilya V. Schurov 

Associate Professor
Image of instructor, Vladimir Podolskii

Vladimir Podolskii 

Associate Professor
Faculty of Computer Science

Start working towards your Master's degree

This course 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.

About National Research University Higher School of Economics

National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more. Learn more on www.hse.ru...

Frequently Asked Questions

  • 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.

  • 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.

  • 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.