- Concentrations and course offerings may vary by campus and/or by program modality. Please consult with your advisor or admissions coach for the course availability each term at your campus or within your program modality.
- Certain options within the program may be required at certain campuses or for certain program modalities. Please consult with your advisor or admissions coach for requirements at your campus or for your program modality.
Complete all courses listed below unless otherwise indicated. Also complete any corequisite labs, recitations, clinicals, or tools courses where specified and complete any additional courses needed beyond specific college and major requirements to satisfy graduation credit requirements.
Universitywide Requirements
All undergraduate students are required to complete the Universitywide Requirements.
NUpath Requirements
All undergraduate students are required to complete the NUpath Requirements.
Data Science Major Requirements
Code | Title | Hours |
---|---|---|
Computer Science Overview | ||
CS 1200 | First Year Seminar | 1 |
CS 1210 | Professional Development for Khoury Co-op | 1 |
Fundamental Courses | ||
CS 1800 and CS 1802 | Discrete Structures and Seminar for CS 1800 | 5 |
Programming Sequence Pathways | ||
Choose one of the two options. | 12 | |
Computer Science Option | ||
Fundamentals of Computer Science 1 and Lab for CS 2500 | ||
Fundamentals of Computer Science 2 and Lab for CS 2510 | ||
Object-Oriented Design and Lab for CS 3500 | ||
Data Science Option | ||
Programming with Data and Data Science Programming Practicum | ||
Intermediate Programming with Data and Lab for DS 2500 | ||
Advanced Programming with Data | ||
Computer Science Required Courses | ||
CS 3000 | Algorithms and Data | 4 |
CS 3200 | Introduction to Databases | 4 |
CS 3520 | Programming in C++ | 4 |
or CS 3650 | Computer Systems | |
Data Science Electives | ||
Complete three of the following: | 12 | |
Artificial Intelligence | ||
Natural Language Processing | ||
Information Retrieval | ||
Human Computer Interaction | ||
Data Science Required Courses | ||
DS 3000 | Foundations of Data Science | 4 |
DS 4200 | Information Presentation and Visualization | 4 |
DS 4300 | Large-Scale Information Storage and Retrieval | 4 |
DS 4400 | Machine Learning and Data Mining 1 | 4 |
DS 4420 | Machine Learning and Data Mining 2 | 4 |
or DS 4440 | Practical Neural Networks | |
Presentation Requirement | ||
Choose one: | 4 | |
Public Speaking | ||
Business and Professional Speaking | ||
Persuasion and Rhetoric | ||
Communication and Storytelling | ||
Improvisation | ||
Introduction to Acting | ||
Dynamic Presence: Theatre Training for Effective Interpersonal Interactions | ||
Acting for the Camera | ||
Mathematics Foundations | ||
MATH 1341 | Calculus 1 for Science and Engineering | 4 |
MATH 1342 | Calculus 2 for Science and Engineering | 4 |
MATH 2331 | Linear Algebra | 4 |
MATH 3081 | Probability and Statistics | 4 |
Data Science and Ethics | ||
PHIL 1145 | Technology and Human Values | 4 |
Khoury Elective Courses | ||
With advisor approval, directed study, research, project study, and appropriate graduate-level courses may also be taken as upper-division electives. | ||
Complete 4 credits of CS, CY, DS, or IS classes that are not already required. Choose courses within the following ranges: | 4 | |
CY 2000 or higher, except CY 4930 | ||
DS 2500 or higher, except DS 4900 | ||
IS 2000 or higher, except IS 4900 | ||
Data Science Related Electives in Other Units | ||
Complete one of the following: | 4 | |
Information Design 1 | ||
Information Design Studio 1: Principles | ||
Information Design History | ||
Research Methods for Design | ||
Visualization Technologies 1: Fundamentals | ||
Information Design Studio 2: Dynamic Mapping and Models | ||
Bioinformatics Computational Methods 1 | ||
Bioinformatics Computational Methods 2 | ||
Statistics for Economists | ||
Applied Econometrics | ||
Computer Vision | ||
Data Visualization | ||
Introduction to Machine Learning and Pattern Recognition | ||
Biostatistics | ||
Game Design and Analysis | ||
Data-Driven Player Modeling | ||
Introduction to Health Informatics and Health Information Systems | ||
Data Management in Healthcare | ||
Personal Health Interface Design and Development | ||
Evaluating Health Technologies | ||
Data Mining for Engineering Applications | ||
Empirical Research Methods | ||
Calculus 3 for Science and Engineering | ||
Statistics and Stochastic Processes | ||
Business Statistics | ||
Data Management for Business | ||
Marketing Research | ||
Marketing Analytics | ||
Information Ethics | ||
AI Ethics | ||
Statistics in Psychological Research | ||
Cognition |
Computer Science Writing Requirement
Code | Title | Hours |
---|---|---|
College Writing | ||
ENGW 1111 | First-Year Writing | 4 |
Advanced Writing in the Disciplines | ||
ENGW 3302 | Advanced Writing in the Technical Professions | 4 |
or ENGW 3315 | Interdisciplinary Advanced Writing in the Disciplines |
Required General Electives
Code | Title | Hours |
---|---|---|
Complete 28 semester hours of general electives. | 28 |
Khoury College GPA Requirement
Minimum cumulative 2.000 GPA required in all CS, CY, DS, and IS courses
NUpath Requirements Satisfied
- Engaging with the Natural and Designed World
- Conducting Formal and Quantitative Reasoning
- Analyzing and Using Data
- Writing in the First Year
- Advanced Writing in the Disciplines
- Writing-Intensive in the Major
- Demonstrating Thought and Action in a Capstone
Integrating Knowledge and Skills Through Experience is satisfied through co-op.
Program Requirement
130 total semester hours required
Sample Plan of Study:
Four Years, Two Co-ops Summer 2/Fall
Year 1 | |||||||
---|---|---|---|---|---|---|---|
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
CS 1200 | 1 | DS 2500 and DS 2501 | 5 | CS 3200 | 4 | MATH 2331 | 4 |
CS 1800 and CS 1802 | 5 | MATH 1342 | 4 | MATH 3081 | 4 | Elective | 4 |
DS 2000 and DS 2001 | 4 | PHIL 1145 | 4 | ||||
ENGW 1111 | 4 | Elective | 4 | ||||
MATH 1341 | 4 | ||||||
18 | 17 | 8 | 8 | ||||
Year 2 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
CS 3520 | 4 | CS 1210 | 1 | CS 3000 | 4 | Co-op | |
DS 3000 | 4 | DS 4200 | 4 | Elective | 4 | ||
DS 3500 | 4 | DS 4300 | 4 | ||||
Presentation Requirement | 4 | Elective | 4 | ||||
Elective | 4 | ||||||
16 | 17 | 8 | 0 | ||||
Year 3 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
Co-op | DS 4400 | 4 | ENGW 3302 | 4 | Co-op | ||
Data Science Elective 2 | 4 | Elective | 4 | ||||
Data Science Elective 1 | 4 | ||||||
Elective | 4 | ||||||
0 | 16 | 8 | 0 | ||||
Year 4 | |||||||
Fall | Hours | Spring | Hours | ||||
Co-op | DS 4420 or 4440 | 4 | |||||
Data Science Related Elective | 4 | ||||||
Data Science Elective 3 | 4 | ||||||
Khoury Elective | 4 | ||||||
0 | 16 | ||||||
Total Hours: 132 |
Four Years, Two Co-ops Spring/Summer 1
Year 1 | |||||||
---|---|---|---|---|---|---|---|
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
CS 1200 | 1 | DS 2500 and DS 2501 | 5 | CS 3200 | 4 | MATH 2331 | 4 |
CS 1800 and CS 1802 | 5 | MATH 1342 | 4 | MATH 3081 | 4 | Elective | 4 |
DS 2000 and DS 2001 | 4 | PHIL 1145 | 4 | ||||
ENGW 1111 | 4 | Elective | 4 | ||||
MATH 1341 | 4 | ||||||
18 | 17 | 8 | 8 | ||||
Year 2 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
CS 1210 | 1 | Co-op | Co-op | Elective | 4 | ||
CS 3520 | 4 | Elective | 4 | ||||
DS 3000 | 4 | ||||||
DS 3500 | 4 | ||||||
Presentation Requirement | 4 | ||||||
17 | 0 | 0 | 8 | ||||
Year 3 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
DS 4200 | 4 | Co-op | Co-op | ENGW 3302 | 4 | ||
DS 4300 | 4 | Elective | 4 | ||||
CS 3000 | 4 | ||||||
Elective | 4 | ||||||
16 | 0 | 0 | 8 | ||||
Year 4 | |||||||
Fall | Hours | Spring | Hours | ||||
DS 4400 | 4 | DS 4420 or 4440 | 4 | ||||
Data Science Elective 1 | 4 | Data Science Related Elective | 4 | ||||
Data Science Elective 2 | 4 | Data Science Elective 3 | 4 | ||||
Elective | 4 | Khoury Elective | 4 | ||||
16 | 16 | ||||||
Total Hours: 132 |