Data Analytics Program (BS)

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Data Analytics is the application of data science to study real-life datasets by mixing statistics, technology, and discipline-specific content knowledge. Students in this program split their coursework between mastering these fundamental skills and courses in one of several possible tracks, focusing their application of these skills to their chosen field of study.

Requirements

A. Core Courses (34-36 credits)

ARI 415 - Ethics and Bias in AI (4)
BUS 115 - Introduction to Business Applications (3)
CSC 179 - Problem Solving and Programming I in Python (4)
ENG 345 - Technical Writing (3)
GIS 203 - Mapping and Spatial Data Science (3)
MTH 118 - Applied Calculus (4)
MTH 220 - Elementary Linear Algebra (4)
One from:
CSC 302 - Introduction to Data Visualization (3-4) , elected for 4 credits
MTH 206 - Elements of Data Science II (3-4) , elected for 4 credits
A course in statistics, from:
MTH 272 - Applied Statistics and Data I (4)
PHS 247 - Public Health Statistics (3)
PSY 322 - Basic Statistics and Probability (4)
SCM 211 - Business Statistics (3)
SOC 215 - General Statistics (3)
SWR 270 - Introduction to Quantitative and Qualitative Data Analysis (4)
One from:
ECN 480 - Quantitative Methods and Econometrics (3)
MTH 306 - Introduction to Data Science (4)
SCM 313 - Introduction to Business Analytics (3)

B. Track of Choice

One of the following tracks:

Business Analytics Track (54 credits)

Track Core (42 credits)

Electives (6 credits)

One from:
FIN 316 - Business Conditions Analysis (3)
SCM 391 - Global Supply Chain Management (3)
One from:
FIN 363 - Investments (3)
FIN 365 - Portfolio Theory and Security Analysis (3)
GIS 271 - GIS for Environmental Management (4)
MKT 332 - Marketing Research (3)
SCM 481 - Global Logistics Management (3)

Capstone/Integration Courses (6 credits)

BUS 394 - Business Internship Experience (1 or 3) , elected for 3 credits
SCM 485 - Advanced Business Analytics (3)
Note: With faculty approval, an independent study involvoing an analytics project may be used to replace the internship course.

Geospatial Analytics Track (36 credits)

Track Core (12 credits)

GIS 404 - Remote Sensing of the Environment (4)
GIS 452 - Introduction to GIS (4)
GIS 453 - Geographic Information Analysis (4)

Electives (16 credits)

At least 16 credits from the following list, in addition to any prerequisite courses required:

BIO 423 - Wildlife Ecology and Management (4)
GIS 271 - GIS for Environmental Management (4)
GIS 401 - Applied GIS for Public Health (4)
GIS 462 - GIS Programming with Python (4)
GIS 484 - WebGIS (4)
GIS 494 - Geospatial Analytics and Modeling (4)
MKT 332 - Marketing Research (3)

Capstone/Integration Courses (8 credits)

Health Data Analytics Track (54-59 credits)

Track Core (34-37 credits)

HCR 212 - Health Care in the United States (3)
HCR 301 - Introduction to Health Information Systems for Administrators (3)
HCR 376 - Health Care Administration (3)
HCR 410 - Health Care Strategic Planning (3)
HCR 477 - Financial Management in Health Care (3)
HCR 478 - Healthcare Quality Management (3)
NSC 373 - Technology in Health Care (3)
MTP 320 - Medical Terminology for Health Professionals (2)
One from:
HCR 304 - The Ethics of Health Care (3)
NSC 180 - Legal and Moral Decisions in Health Care (3)
One from:
HCR 305 - Public Policy and Health Care (3)
NUR 370 - Health Policy for Nursing (2)
One from:
HCR 370 - Healthcare Professionalism and Leadership (3)
NUR 420 - Nursing Leadership and Management (5)
One from:
HCR 385 - Health Care Program Evaluation (3)
NUR 316 - Research in Nursing (3)

Electives (6 credits)

At least 6 credits from:

Capstone/Integration Courses (14-16 credits)

GIS 401 - Applied GIS for Public Health (4)
HCR 480 - Analytic Solutions to Healthcare Problems (4)
NSC 452 - Legal and Ethical Applications of Health Information (3)
One from:
PHS 315 - Introduction to Epidemiology (3)
NSC 402 - Epidemiology and Disease Prevention (2)
One from:
NUR 345 - Nursing and Healthcare Informatics (2)
PHS 467 - Health Information Management (3)

Social Analytics Track (48 credits)

Track Core (15 credits)

At least 15 credits from:

Electives (27 credits)

At least 27 additional credits in social sciences courses, which may include prerequisites for track core courses.

Capstone/Integration Courses (6 credits)

At least 6 additional credits, to include:

One from:
CRJ 399 - Criminal Justice Internship (3-6)
GIS 401 - Applied GIS for Public Health (4)
GIS 491 - Transportation Planning and Analysis (4)
PSY 360 - Internship in Psychology (1-3)
PSY 401 - Advanced Research Experience (4)
SWR 460 - Field Instruction I (6)
SWR 470 - Advanced Approaches to Social Work Research (3)
URP 498 - Internship (3)
Note: With faculty approval, an independent study involving an analytics project may also be allowed.
One additional from:
ANT 499 - Senior Seminar (3)
CRJ 450 - Senior Seminar in Criminal Justice (3)
PSY 400 - Advanced Topics in Psychology (4)
PSY 401 - Advanced Research Experience (4)
SOC 499 - Senior Seminar (3)
SWR 490 - Integrative Seminar in Social Work, Global Justice and Diversity (3-4)

C. Additional Requirements

All requirements of the College of Innovation and Technology (CIT) Bachelor of Science degree, including General Education requirements and University of Michigan-Flint graduation requirements .

Minimum Credits for the Degree: 120 credits

Honors Program

All bachelor-degree-seeking students with GPAs of 3.5 or higher are eligible to apply to the University of Michigan-Flint Honors Program . Please contact the Honors Program Manager or the Honors Program Director for further information.