The Bachelor of Science in Data Science studies the collection, manipulation, storage, retrieval, and computational analysis of data in its various forms, including numeric, textual, image, and video data from small to large volumes.
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.
University-Wide Requirements
All undergraduate students are required to complete the University-Wide 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 | Database Design | 4 |
CS 3520 | Programming in C++ | 4 |
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 |
DS 4440 | Practical Neural Networks | 4 |
Presentation Requirement | ||
Choose one: | 4 | |
Public Speaking | ||
Business and Professional Speaking | ||
Persuasion and Rhetoric | ||
Communication and Storytelling | ||
Improvisation | ||
Introduction to Acting | ||
The Professional Voice | ||
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 | ||
Data Science Related Electives in Other Units | 4 | |
Complete one of the following: | ||
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 | ||
Information Design Studio 3: Synthesis | ||
Bioinformatics Computational Methods 1 | ||
Bioinformatics Computational Methods 2 | ||
Statistics | ||
Applied Econometrics | ||
Advanced Engineering Algorithms | ||
Computer Vision | ||
Data Visualization | ||
Introduction to Machine Learning and Pattern Recognition | ||
Biostatistics | ||
Advanced Financial Strategy | ||
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 | ||
Empirical Research Methods | ||
Data Mining for Engineering Applications | ||
Calculus 3 for Science and Engineering | ||
Statistics and Stochastic Processes | ||
Business Statistics | ||
Data Management in the Enterprise | ||
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 24 credits of general electives. | 24 |
Khoury College GPA Requirement
Minimum 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 Patterns:
Four Years, Two Co-ops
Year 1 | |||||||
---|---|---|---|---|---|---|---|
Fall | Hours | Spring | Hours | Summer 1 | Hours | ||
CS 1200 | 1 | DS 2500 and DS 2501 | 5 | CS 3200 | 4 | ||
CS 1800 and CS 1802 | 5 | MATH 1342 | 4 | MATH 3081 | 4 | ||
DS 2000 and DS 2001 | 4 | PHIL 1145 | 4 | ||||
ENGW 1111 | 4 | Elective | 4 | ||||
MATH 1341 | 4 | ||||||
18 | 17 | 8 | |||||
Year 2 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
CS 3520 | 4 | DS 4200 | 4 | CS 3000 | 4 | Co-op | |
DS 3000 | 4 | DS 4300 | 4 | ENGW 3302 | 4 | ||
MATH 2331 | 4 | IS 4300 | 4 | ||||
DS 3500 | 4 | Elective | 4 | ||||
CS 1210 | 1 | ||||||
16 | 17 | 8 | 0 | ||||
Year 3 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
Co-op | DS 4400 | 4 | Co-op | Co-op | |||
CS 4100 | 4 | ||||||
Presentation Requirement | 4 | ||||||
Elective | 4 | ||||||
0 | 16 | 0 | 0 | ||||
Year 4 | |||||||
Fall | Hours | Spring | Hours | ||||
IS 4200 | 4 | DS 4420 | 4 | ||||
CS 4120 | 4 | DS 4440 | 4 | ||||
Khoury Elective | 4 | Data Science Related Elective | 4 | ||||
Elective | 4 | Elective | 4 | ||||
16 | 16 | ||||||
Total Hours: 132 |
Five Years, Three Co-ops in Summer 2/Fall
Year 1 | |||||||
---|---|---|---|---|---|---|---|
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
CS 1200 | 1 | DS 2500 and DS 2501 | 5 | Vacation | Vacation | ||
DS 2000 and DS 2001 | 4 | MATH 1342 | 4 | ||||
CS 1800 and CS 1802 | 5 | CS 3200 | 4 | ||||
MATH 1341 | 4 | PHIL 1145 | 4 | ||||
ENGW 1111 | 4 | ||||||
18 | 17 | 0 | 0 | ||||
Year 2 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
DS 3000 | 4 | CS 1210 | 1 | Vacation | Co-op | ||
CS 3000 | 4 | CS 3520 | 4 | ||||
MATH 3081 | 4 | DS 4300 | 4 | ||||
DS 3500 | 4 | IS 4300 | 4 | ||||
MATH 2331 | 4 | ||||||
16 | 17 | 0 | 0 | ||||
Year 3 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
Co-op | DS 4400 | 4 | ENGW 3302 | 4 | Co-op | ||
Presentation Requirement | 4 | Elective | 4 | ||||
CS 4100 | 4 | ||||||
DS 4200 | 4 | ||||||
0 | 16 | 8 | 0 | ||||
Year 4 | |||||||
Fall | Hours | Spring | Hours | Summer 1 | Hours | Summer 2 | Hours |
Co-op | DS 4420 | 4 | Elective | 4 | Co-op | ||
CS 4120 | 4 | Elective | 4 | ||||
IS 4200 | 4 | ||||||
Elective | 4 | ||||||
0 | 16 | 8 | 0 | ||||
Year 5 | |||||||
Fall | Hours | Spring | Hours | ||||
Co-op | DS 4440 | 4 | |||||
Data Science Related Elective | 4 | ||||||
Elective | 4 | ||||||
Elective | 4 | ||||||
0 | 16 | ||||||
Total Hours: 132 |