Skagit Valley College

Catalog Course Search Details

New Course: this course was added after the last catalog

 Course Title:   Discrete Structures I

 Title Abbreviation:   DISCRETE STRUCTURES I

 Department:    CS

 Course #:    202

 Credits:    5

 Variable:     No

 IUs:    5

 CIP:    11.0701

 EPC:    CSACSBS

 REV:    2024


 Course Description  

Set theory, relations, functions, formal logic, constructing proofs, computing with base-n numbers, combinatorics, and discrete probability with applications.

 Prerequisite  

Prerequisite: CS 171 with grade C or higher.

Additional Course Details

Contact Hours (based on 11 week quarter)

Lecture: 55

Lab: 0

Other: 0

Systems: 0

Clinical: 0


Intent: Distribution Requirement(s) Status:  

Academic N/A  

Equivalencies At Other Institutions

Other Institution Equivalencies Table
Institution Course # Remarks
N/A

Learning Outcomes

After completing this course, the student will be able to:

  1. Use logical notation to define and reason about fundamental mathematical concepts such as sets, relations, functions, and integers.
  2. Formulate induction hypotheses and write simple proofs, including induction and other techniques.
  3. Use the elementary properties of modular arithmetic and explain their applications in computer science such as cryptography, hashing algorithms.
  4. Calculate the possible outcomes of combinatorial processes such as permutations and combinations.
  5. Calculate probabilities and discrete distributions for simple combinatorial processes.

General Education Learning Values & Outcomes

Revised August 2008 and affects outlines for 2008 year 1 and later.

Course Contents

  1. Logical notations and fundamental mathematical concepts such as sets, relations, functions, and integers.
  2. Induction hypotheses and simple proofs, including induction and other techniques.
  3. Elementary properties of modular arithmetic and applications in computer science such as cryptography, hashing algorithms.
  4. Possible outcomes of combinatorial processes such as permutations and combinations.
  5. Probabilities and discrete distributions for simple combinatorial processes.