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Mathematical Thinking in Computer Science

Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. In this...

By Alexander S. Kulikov on Coursera

About This Course

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 online 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.

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Frequently Asked Questions

How much does Mathematical Thinking in Computer Science cost?

Visit the Mathematical Thinking in Computer Science course page for current pricing and available discounts.

Who teaches Mathematical Thinking in Computer Science?

Mathematical Thinking in Computer Science is taught by Alexander S. Kulikov, University of California San Diego.

What skill level is Mathematical Thinking in Computer Science for?

This course is designed for all levels learners.

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Students0
Duration5 hours
LevelAll Levels
Languageen
PlatformCoursera