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Introduction to Discrete Mathematics for Computer Science

University of California, San Diego via Coursera Specialization


Discrete Mathematics is the language of Computer Science. One needs to be fluent in it to work in many fields including data science, machine learning, and software engineering (it is not a coincidence that math puzzles are often used for interviews). We introduce you to this language through a fun try-this-before-we-explain-everything approach: first you solve many interactive puzzles that are carefully designed specifically for this online specialization, and then we explain how to solve the puzzles, and introduce important ideas along the way. We believe that this way, you will get a deeper understanding and will better appreciate the beauty of the underlying ideas (not to mention the self confidence that you gain if you invent these ideas on your own!). To bring your experience closer to IT-applications, we incorporate programming examples, problems, and projects in the specialization.


Course 1: Mathematical Thinking in Computer Science
- Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine ... Enroll for free.

Course 2: Combinatorics and Probability
- Counting is one of the basic mathematically related tasks we encounter on a day to day basis. The main question here is the following. If we ... Enroll for free.

Course 3: Introduction to Graph Theory
- We invite you to a fascinating journey into Graph Theory — an area which connects the elegance of painting and the rigor of mathematics; is ... Enroll for free.

Course 4: Number Theory and Cryptography
- We all learn numbers from the childhood. Some of us like to count, others hate it, but any person uses numbers everyday to buy things, pay ... Enroll for free.

Course 5: Delivery Problem
- We’ll implement (in Python) together efficient programs for a problem needed by delivery companies all over the world millions times per day ... Enroll for free.


Taught by

Alexander S. Kulikov, Michael Levin and Vladimir Podolskii

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