Find out more about available formats and browse any associated online resources. Computer science majors taking a non-programming-based course like discrete mathematics might ask 'Why do I need to ...

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This course will discuss fundamental concepts and tools in discrete mathematics with emphasis on their applications to computer science. Example topics include logic and Boolean circuits; sets, ...

Growing areas like machine learning require expertise in programming, data science and related fields. Statistical, mathematical, data science and computing experts are needed in an economy that ...

The Bachelor of Science in Mathematics at Michigan Tech develops confident, tech-focused problem solvers adept at understanding mathematical concepts. The core curriculum covers a variety of topics, ...

A BS in Mathematics and Computer Science from Michigan Tech can help hone your approach to computational problem solving, preparing you for a successful career in the 21st century. After earning ...

Lecturers: Linda Burks, Katelyn Byington, Will Dana, Joshua Grice, Corey Irving, Phillip Jedlovec, Mary Long, Norman Paris, Luvreet Sangha, George Schaeffer The Department of Mathematics and Computer ...

The Department has a strong faculty working in various topics in discrete mathematics, especially algorithmic aspects. The interface between Theoretical Computer Science and Discrete Mathematics has ...

Taking an approved discrete mathematics prerequisite course is also encouraged because it significantly increases the number of course options students have for completing their Upper-Division CSCI ...

Note: This course description is only applicable for the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

This is a graduate-level course focused on techniques and models in modern discrete probability. Topics include: the first and second moment methods, martingales, concentration inequalities, branching ...