Dec 06, 2023
2019-2020 Course Catalog
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# CSCI 2014 - Discrete Structures of Computer Science

Credits: 4
Hours/Week: Lecture 4 Lab None
Course Description: This course covers discrete mathematical techniques and structures used in computer science. The content stresses problem solving techniques that involve the use of logic, various methods of proof, and sets. Topics of particular interest to computer scientists include big-O notation, recursion, and the fundamentals of trees and graphs.
MnTC Goals
None

Prerequisite(s): Course placement into MATH 1081  or completion of MATH 1061  with a grade of C or higher.
Corequisite(s): None
Recommendation: None

Major Content
1. Logic and proof
2. Mathematical induction, including both strong and weak induction
3. Elementary set theory
4. Relations and functions
5. Recurrence relations
6. Elementary number theory and applications
7. Elementary graph theory and applications
8. Combinatorics and probability
9. Algorithm analysis

Learning Outcomes
At the end of this course students will be able to:

1. describe how symbolic logic can be used to model real-life situations or applications, including those arising in computing contexts such as software analysis (e.g., program correctness), database queries, and algorithms.
2. examine the logical validity of arguments and proofs as they apply to Boolean expressions.
3. apply mathematical induction and other techniques to prove mathematical results.
4. perform computations using recursively defined functions and structures.
5. solve problems involving sets, relations, functions, and congruences.
6. illustrate the basic terminology and properties of graphs and trees.
7. use graphs and trees to solve problems algorithmically.
8. use methods of combinatorics to solve counting and basic probability problems.

Competency 1 (1-6)
None
Competency 2 (7-10)
None

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