Discrete Mathematics Online Course for Academic Credit
| 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
Distance Calculus - Student Reviews
The pace of a traditional classroom setting was just too quick for the concepts to really sink in. With Distance Calculus, I had courses that were taught with the full rigor of an on-campus class, but where I could take my time and really learn the material...all while having access to top-tier instructional help for real math professors and assistants.
DC gave me the tools and the confidence I needed, so after successfully passing my DC courses, I moved on and completed a master's degree in CS.


