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Mathematical Thinking in Computer Science

Discrete Math is needed to see mathematical structures in the object you work with, and understand their properties. This ability is important for software engineers, data scientists, security and financial analysts (it is not a coincidence that math puzzles are often used for interviews). We cover the basic notions and results (combinatorics, graphs, probability, number theory) that are universally needed. To deliver techniques and ideas in discrete mathematics to the learner we extensively use interactive puzzles specially created for this specialization. To bring the learners experience clo

4.2
121 reviews

Created by: Alexander S. Kulikov

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Course Description

Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. In this course, we will learn the most important tools used in discrete mathematics: induction, recursion, logic, invariants, examples, optimality. We will use these tools to answer typical programming questions like: How can we be certain a solution exists? Am I sure my program computes the optimal answer? Do each of these objects meet the given requirements?In the course, we use a try-this-before-we-explain-everything approach: you will be solving many interactive (and mobile friendly) puzzles that were carefully designed to allow you to invent many of the important ideas and concepts yourself.Prerequisites: 1. We assume only basic math (e.g., we expect you to know what is a square or how to add fractions), common sense and curiosity. 2. Basic programming knowledge is necessary as some quizzes require programming in Python.Do you have technical problems? Write to us: coursera@hse.ru
Read More product length iconTime: 25h

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Instructor Details

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Alexander S. Kulikov is a research fellow at St. Petersburg Department of Steklov Mathematical Institute of the Russian Academy of Sciences and a visiting professor at University of California, San Diego. His scientific interests include algorithms for NP-hard problems and circuit complexity. In St. Petersburg, he runs Computer Science Club and Computer Science Center.

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Reviews

4.2

121 reviews in total

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By BAPPADITYA D on 24-Oct-19

I like this course as this course forced me to think for some existing challenges in a research oriented approach. Mathematics is fun and this course again prove this popular concept again. I am eager to learn more and cover future courses for the specialization.

By Alberto B on 23-Oct-19

Good concepts to know and nice examples

By Omar E A on 23-Oct-19

the puzzles are fun to solve

By Trần C L on 19-Oct-19

Good course with many interesting quizzes although it is lacking of clear explanation

By Marco F on 18-Oct-19

It felt more like learning how to do puzzles rather than learning math. But maybe that was the objective and I didn't get it!

By HAILEMICHAEL Y M on 12-Oct-19

The course is very good at equipping the basic math concepts for computer science. I highly recommend it!

By John A B on 4-Oct-19

I followed along pretty well but there where a few parts that the instructors just sort of hand waved the developing the formula's needed to solve the theorems. Also the programming questions where always clear about how they wanted the return object represented. This led to some try and error, falling the question to see what little feed back it would give, making a change to the subroutine and then trying again.

By Mingzhe H on 26-Sep-19

There are many funny puzzles in this course.But i think the diffcult so low.assume you don't know how to proof it,you also can use force to find the answer.the knowledge of this course so wide,but not deep.of course the team are very hard,i wish you can continue to push out more course to improve us,Thanks for your efforts.

By Hearan on 17-Sep-19

The quiz were all very interesting, but sometimes it was hard to understand the lecturers...

By Amer A on 15-Sep-19

very useful and impressive

By evans on 9-Sep-19

very good

By Mahavishnu R on 7-Sep-19

Puzzles are great. Seems Instructors put lots of efforts into it. Different approach !

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Overall Score : 84 / 100

Mathematical Thinking in Computer Science
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  • Video Duration: icon 25h
  • Price: Free
  • Provider: icon Coursera
  • University: icon Imperial College London
  • Language: icon English
  • Certificate: icon Yes

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