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Computer Science: Software Engineering (BS)

Computer Science Bachelors BS

Variable Credit Min

74

Variable Credit Max

76

Major Academic Plan

Title

Computational Practice

Learning Outcome

Students will design and implement significant computer programs using a combination of design, implementation, documentation, and testing.

Title

Computational Theory

Learning Outcome

Students will analyze problems and their algorithmic solutions using theoretical concepts.

Title

Diversity, Equity, and Inclusion

Learning Outcome

Students experience a spirit of belonging and have access to the resources they need to succeed. All students are welcome, including those traditionally underrepresented in CS programs and those new to programming.

Title

Career Preparation

Learning Outcome

Students will have sufficient maturity in computer science to work in a professional setting in computer science or software engineering or to enter a graduate program.

Program Requirements

Grades below C- are not allowed in major courses.

Requirement 1 — Complete 17 Courses

Core courses:

course - Intro to Computer Science 3.0

course - Software Engineering Lab 1 1.0

course - Software Engineering Lab 2 1.0

course - Software Engineering Lab 3 1.0

course - Computer Systems 3.0

course - Data Structures 3.0

course - Discrete Structure 3.0

course - Adv Software Construction 4.0

course - Web Programming 3.0

course - Algorithm Design & Analysis 3.0

course - Systems Programming3.0

course - Test, Analysis, & Verification3.0

course - Software Design3.0

course - Ethics & Computers in Society2.0

course - Database Modeling Concepts3.0

course - Soft Eng Capstone 13.0

course - Soft Eng Capstone 23.0

Requirement 2 —Complete 4 Courses

course - Calculus 14.0

course - Elementary Linear Algebra 2.0

course - Computational Linear Algebra 1.0

course - Intro to Newtonian Mechanics3.0

course - Technical Communication3.0

Requirement 3 — Complete 1 of 2 Courses

course - Principles of Statistics 3.0

course - Stat for Engineers & Scientist 3.0

Requirement 4 — Complete 1 of 3 Courses

course - Calculus 2 4.0

course - Fundamentals of Mathematics 3.0

course - Stat Modeling for Data Science 3.0

Requirement 5 — Complete 2 of 11 Courses

course - Introduction to HCI 3.0

course - Concepts of Programng Lang 3.0

course - Operating Systems Design 3.0

course - Advanced Techniques in HCI 3.0

course - Fund of Information Retrieval 3.0

course -Mobile and Ubiquitous HCI 3.0

course - Comp Comms & Networking 3.0

course - Distributed System Design 3.0

course - Computer Security 3.0

course - Intro to Machine Learning 3.0

course - Verification and Validation 3.0

Requirement 6 — Complete 1 of 38 Courses

Courses will not double count between Requirement 5 and Requirement 6.

course - Intro to Computational Theory 3.0

course - Introduction to HCI 3.0

course - Concepts of Programng Lang 3.0

course - Operating Systems Design 3.0

course - Graphics and Image Processing 3.0

course - Advanced Techniques in HCI 3.0

course - Adv Algorithms & Probl Solving 3.0

course - Topics in Computer Science - You may take up to 3.0 credit hours 1.0v

course - Software Business 3.0

course - Linear Prog/Convx Optimization 3.0

course - Computer Vision 3.0

course - Fund of Information Retrieval 3.0

course - Computer Graphics 3.0

course - Mobile and Ubiquitous HCI 3.0

course - Comp Comms & Networking 3.0

course - Distributed System Design 3.0

course - Computer Security 3.0

course - Blockchain Technologies 3.0

course - Intro Artificial Intelligence 3.0

course - Voice Interfaces 3.0

course - Intro to Machine Learning 3.0

course - Deep Learning 3.0

C S 478 - Tools for Machine Learning - This course is no longer available for registration and will count only if you completed it while it was offered. Please see your college advisement center for possible substitutions. 3.0

course - Intro to Machine Translation 3.0

course - Verification and Validation 3.0

course - Computing Competitions - You may take up to 3.0 credit hours 3.0

course - Undergraduate Research - You may take up to 6.0 credit hours 3.0

course - Undergraduate Special Projects - You may take up to 3.0 credit hours 1.0v

course - Adv Topics in Computer Sci - You may take up to 3.0 credit hours 1.0v

course - Robust Control 3.0

C S 575 - Intro to Network Science - This course is no longer available for registration and will count only if you completed it while it was offered. Please see your college advisement center for possible substitutions. 3.0

course - Theory of Predictive Modeling 3.0

course - Computer Systems 4.0

course - Real-Time Operating Systems 4.0

course - Cybersecurity & Pen Test 3.0

course - Numerical Methods 3.0

course - Probability Theory 3.0

course - Mathematical Cryptography 3.0

Note: If C S 493R, C S 498R, or C S 501R is chosen, it must be taken for 3 credit hours.

Requirement 7 — Obtain confirmation from your advisement center that you have completed the following:

Complete Senior Exit interview with the C S department during last semester or term.

Note: Math 112, Math 113, Phscs 121, WRTG 316, and C S 312 can be used to fill both General Education and program requirements. Advanced Writing and Oral Communication: WRTG 316. Quantitative Reasoning: Math 112 or 113. Languages of Learning: Math 112 or 113. Physical Science: C S 312 or Phscs 121.