Computer Science
 

Computer Science: Data Science

Computer Science: Data Science
BS
Hours74 Credit Hours
MAPMajor Academic Plan

Program Requirements

Grades below C- are not allowed in major courses.
requirement 1 Complete 11 courses
requirement 2 Complete 4 courses
requirement 3 Complete 1 option
option 3.1 Complete 1 course
MATH 313 - (Not currently offered)
option 3.2 Complete 2 courses
requirement 4 Complete 1 course
requirement 5 Complete 1 course
requirement 6 Complete 3.0 hours from the following course(s)
requirement 7 Complete 12.0 hours from the following course(s)
Note: C S 494/495, the capstone courses, are strongly recommended.
Note: Students can take C S 401R or C S 501R more than once.
Note: Total hours for C S 497R across all requirements cannot exceed 6.0.
Note: If C S 494 or 495 are chosen in Requirements 7 or 8, students should complete the sections designated for the Data Science emphasis.
Note: For requirements 7 and 8, students may only take C S 494 and 495, or C S 482 and 483.
requirement 8 Complete 3.0 hours from the following course(s)
Note: Courses taken to fulfill Requirements 4 and 5 cannot double count here.
C S 252 - Introduction to Computational Theory 3.0
C S 329 - Testing, Analysis, and Verification 3.0
C S 330 - Concepts of Programming Languages 3.0
C S 340 - Software Design and Testing 3.0
C S 345 - Operating Systems Design 3.0
C S 355 - Interactive Graphics and Image Processing 3.0
C S 356 - Designing the User Experience 3.0
C S 401R - Topics in Computer Science 3.0v
You may take up to 3 credit hours.
C S 412 - Linear Programming and Convex Optimization 3.0
C S 418 - Bioinformatics 3.0
C S 450 - Computer Vision 3.0
C S 453 - Fundamentals of Information Retrieval 3.0
C S 455 - Computer Graphics 3.0
C S 456 - Introduction to User Interface Software 3.0
C S 460 - Computer Communications and Networking 3.0
C S 462 - Large-Scale Distributed System Design 3.0
C S 465 - Computer Security 3.0
C S 470 - Introduction to Artificial Intelligence 3.0
C S 482 - (Not currently offered)
C S 483 - (Not currently offered)
C S 486 - Verification and Validation 3.0
C S 494 - Capstone 1 3.0
C S 495 - Capstone 2 3.0
C S 497R - Undergraduate Research 3.0
You may take this course up to 1 time.
C S 501R - Advanced Topics in Computer Science 3.0v
You may take up to 3 credit hours.
ECON 378 - Statistics for Economists 3.0
ECON 388 - Introduction to Econometrics 3.0
ECON 488 - Applied Econometrics 3.0
ECON 588 - Advanced Econometrics 3.0
LING 581 - Natural Language Processing 3.0
MATH 314 - Calculus of Several Variables 3.0
MATH 413 - Advanced Linear Algebra 3.0
STAT 240 - Probability and Inference 1 3.0
STAT 251 - Introduction to Bayesian Statistics 3.0
STAT 340 - Probability and Inference 2 3.0
requirement 9
Complete Senior Exit Interview with the Computer Science department during last semester or term.
Note: Math 112, Math 113, Phscs 121, Engl 316, and C S 312 can be used to fill both General Education and program requirements. Advanced Writing and Oral Communication: Engl 316. Quantitative Reasoning: Math 112 or 113. Languages of Learning: Math 112 or 113. Physical Science: C S 312 or Phscs 121.
Program Outcomes: 

Computational Practice:

Students will design and implement significant computer programs that meet a human need and will develop expertise in data science.

Computational Theory:

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

Career Preparation

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

Diversity, Equity, and Inclusion

Our program is accessible to everyone, including women, minorities, and those new to programming, and provides an equal opportunity for every student to succeed.