Discrete Mathematics Online Course for Academic Credit


ENROLLMENT STARTS Spring 2026





Course Title: Computational Discrete Mathematics
Catalog Number: DMAT 225
Credits: 4 Semester Credit Hours
Syllabus PDF: PDF Syllabus for Computational Discrete Mathematics
Delivery: Fully Online, Asynchronous, Self-Paced
Click Here to Enroll in DMAT 225 - Computational Discrete Mathematics


Roger Williams University Course Catalog Listing: DMAT 225 - Computational Discrete Mathematics

Course: DMAT 225

Course Title: Computational Discrete Mathematics

Transcript Course Title (30 Characters Max:): Comp Discrete Math

Course Description: A single course on discrete mathematics with emphasis on the connections to computer science. Topics include sets, functions, mathematical induction, sequences, recurrence relations, logic, proofs, and introductions to combinatorics and number theory. [4 Semester Credits]

Prerequisite: Successful completion (C- or higher) of Precalculus with Trigonometry or equivalent, or consent of instructor.

E-Textbook: Computational Discrete Mathematics by Skiena/Pemmaraju Discrete Mathematics and Its Applications by Kenneth Rosen, 7th

Software: Mathematica

PDF Course Syllabus: Detailed Course Syllabus in PDF for DMAT 225 - Computational Discrete Mathematics


DMAT 225 - Computational Discrete Mathematics - Learning Outcomes

  • 1. To develop understanding and ability in symbolic logic
  • 2. To understand and formulate basic mathematical proofs
  • 3. To understand and formulate mathematical conjecture and algorithmic experimentation
  • 4. To understand and compute the core concepts of Set Theory
  • 5. To develop understanding of introductory Number Theory and Cryptography
  • 6. To understand and formulate induction and recursion proofs and computations
  • 7. To understand and compute with the Principals of Counting and Recurrence Relations
  • 8. To develop understanding of introductory Graph and Tree Theory


DMAT 225 - Computational Discrete Mathematics - Syllabus of Topics

1.	Getting Started
	1.1.  Email and Chat
	1.2.  Learning About the Course
	1.3   Required Hardware
	1.4.  Software Fundamentals

2.	Logical Reasoning
	2.1.	Propositional Logic
	2.2.	Equivalences
	2.3.	Inference
	2.4.	Introduction to Proofs
	2.5.	Proof Methods and Strategies
	2.6.	Conjecture and Experimentation

3.	Set Theory
	3.1.	Sets and Set Operations
	3.2.	Functions
	3.3.	Sequences and Summations
	3.4.	Matrices

4.	Algorithms
	4.1.	Introduction
	4.2.	Growth of Functions
	4.3.	Complexity of Algorithms
	
5.	Number Theory
	5.1.	Modular Arithmetic
	5.2.	Divisibility
	5.3.	Primes
	5.4.	Greatest Common Divisors
	5.5.	Congruences
	5.6.	Cryptography

6.	Recursion
	6.1.	Danger in Recursion in Programming
	6.2.	Induction
	6.3.	Recursion and Algorithms
	
7.	Counting
	7.1.	Basics of Counting
	7.2.	Pigeonhole Principle
	7.3.	Permutations
	7.4.	Combinations
	7.5.	Recurrence Relations
	7.6.	Divide-and-Conquer Algorithms
	
8.	Relations
	8.1.	Properties of Relations
	8.2.	Closure
	8.3.	Equivalence
	
9.	Graph Theory
	9.1.	Graphs and Graph Models
	9.2.	Generating Graphs
	9.3.	Representing Graphs and Graph Isomorphism
	9.4.	Connectivity
	9.5.	Euler and Hamilton Paths
	9.6.	Graph Coloring
	9.7.	Trees



	





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