Computer Science: AS

Associate of Science | 60 credits

Program Website
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Program Description

The Computer Science AS degree prepares students for transfer to Utah universities and various computing careers. The degree emphasizes Computer Science, Data Science, and Software Development. With a careful selection of elective emphasis area courses, the student can transfer and continue their studies toward a bachelor’s degree as a Junior.

Career Opportunities

The Computer Science AS degree primarily prepares student for transfer to programs leading to a bachelor’s degree. A bachelor’s degree in computer science or related areas leads to many different career opportunities:

Based upon the job postings in Glass Door, in September 2024 there were 262 postings for individuals with Computer Science degrees. The salaries ranged from 40K - 200K and include careers such as Programmer/Analyst, Software Engineer, Applications Developer, Implementation Technician, etc.

https://www.glassdoor.com/Job/salt-lake-city-ut-computer-science-jobs-SRCH_IL.0,17_IC1128289_KO18,34.htm?maxSalary=200000&minSalary=40000

Transfer/Articulation Information

Please refer to the Student Resources section of the SLCC University Transfer webpage.

Estimated Cost for Students

Tuition and student fees: http://www.slcc.edu/student/financial/tuition-fees.aspx

Books: $300, Supplies: $0-$100, Course Fees: $100

Note: Fees vary based upon specific registration and are subject to changes.

General Education Requirements

Associate of Science (AS) / Associate of Arts (AA) Degree General Education Requirements

Program General Education Notes

Courses that meet General Education requirements may be used to meet program requirements unless specified by the program. If this option is chosen, students must complete additional general elective courses to meet the total credit hour requirement.

Program Requirements

Required Courses (12 credits)

If beginning program with no prior programming experience, complete CS 1030 - Foundations of Computing as a program elective prior to starting the required courses below.

Complete all of the following:

Program Electives (21 credits)

Students may take any combination of the below courses. The groupings are guides to student choice for transfer.

CS 1030 - Foundations of Computing (complete if beginning program with no prior programming experience)
Computer Science Elective Recommendations:
CS 2430 - Discrete Structures
CS 2450 - Software Engineering
CS 2810 - Computer Architecture
Data Science Elective Recommendations:
CS 2500 - Data Wrangling
CSIS 1550 - SQL Programming
Software Development Elective Recommendations:
CS 2370 - C++ Programming
CSIS 1250 - Network Routing and Switching I
CSIS 1430 - Internet & XHTML Fundamentals
CSIS 2440 - Web Programming
Additional Transfer Course Elective Recommendations:
BIOL 1610 - College Biology I (LS)
CHEM 1210 - General Chemistry I
ENGR 1010 - Engineering Math Techniques
ENGR 2550 - Applied Probability & Statistics for Engineers
MATH 1040 - Intro to Statistics (QL)
MATH 1050 - College Algebra (QL)
MATH 1080 - Precalculus (QL)
MATH 1210 - Calculus I (QL)
MATH 1220 - Calculus II
MATH 2200 - Introduction to Discrete Mathematics
MATH 2210 - Multivariate Calculus
MATH 2270 - Linear Algebra
PHYS 2010 - College Physics I
PHYS 2015 - College Physics Lab I
PHYS 2210 - Physics for Science & Engineering I
PHYS 2215 - Physics for Sci & Eng Lab I

Time to Completion & Graduation Map

Computer Science AS: Full-time
Time to completion is 4 semesters based on a full-time minimum of 15-16 credits per semester. Less than 15 credits per semester will increase time to completion.

Program Learning Outcomes

Program learning outcome alignment with Student Learning Outcomes in brackets.

Demonstrate substantive knowledge in computer science, including classical algorithms, data structures, and programming languages. [1,9]
Apply principles of data structures, algorithms, and graphical user interfaces in the context of object-oriented design to develop modular, reusable, and maintainable code. [4,5]
Analyze the complexity and efficiency of algorithms using quantitative literacy and computational thinking. [1,3]
Apply software development principles including requirements analysis, software design, implementation, testing and modification for software projects. [1,5]
Collaborate effectively in teams to develop software solutions, demonstrating effective communication in technical and professional contexts utilizing collaborative development tools. [2,7]
Articulate the responsibilities of a computer science professional including the ethical and social issues. [6,8]