Introduction to Discrete Mathematics for Computer Science

This discrete-mathematics specialization introduces ideas through problems and puzzles before explaining the general methods behind them. Proofs, counting, probability, and graphs connect to computing examples. It is a useful shift from asking whether a program seems to work toward asking why an approach should work at all.

What you will learn

• Develop and explain mathematical arguments
• Solve counting and probability problems
• Model relationships with graphs
• Connect discrete mathematics to programming problems

Who this suits

Useful for a programmer or computer-science student who wants stronger mathematical foundations. Some algebra and basic Python experience will help with the programming examples. Expect unfamiliar problems to take time; productive struggle is part of this subject rather than a sign that another video is missing.

Before you enroll

A correct answer without a justification leaves much of the learning unfinished. Write down assumptions and test small cases, then explain why the reasoning extends beyond those examples. This is a foundation for algorithms and theory, not a replacement for all university mathematics requirements.

Full specialization and certificate access generally require paid Coursera enrollment. Check current preview, trial, and financial-aid availability.

Put it into practice

Solve a small graph problem by enumeration, then compare that result with a general argument and explain where brute force becomes impractical.

Source and review

This overview is based on the provider's published information, checked on 11 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

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