Data Science, MS Analytics Management Specialization
As the strategic and tactical decisions of organizations become increasingly data-driven, analytics managers bridge the work of analysts and modelers with business operations and strategy to lead data science teams, address future business needs, identify business opportunities, and translate the work of data scientists into language that business management understands. This specialization equips data scientists with the communication and management strategies needed to be data-driven leaders who utilize models, analyses, and statistical data to improve business performance.
Curriculum
Core Courses (8 units)
Course | Title |
---|---|
MSDS 400-DL | Math for Modelers |
MSDS 401-DL/401-0 | Applied Statistics with R |
MSDS 420-DL/420-0 | Database Systems |
MSDS 422-DL/422-0 | Practical Machine Learning |
MSDS 460-DL/460-0 | Decision Analytics |
MSDS 485-DL/485-0 | Data Governance, Ethics, and Law |
MSDS 498-DL/498-0 | Capstone Class |
or MSDS 590-DL | Thesis Research |
Any one of the following: 1 | |
Research Design for Data Science | |
Data Science and Digital Transformation | |
Technology Entrepreneurship | |
Management Consulting | |
Accounting and Finance for Technology Managers | |
Project Management | |
Business Process Analytics | |
Business Leadership and Communications |
- 1
Students need to choose one of these eight course options to fulfill the business, leadership, communication requirement. A student cannot fulfill a core and specialization requirement with the same course.
Specialization Courses (4 units)
Course | Title |
---|---|
MSDS 474-DL | Accounting and Finance for Technology Managers |
MSDS 476-DL/476-0 | Business Process Analytics |
Any two electives | |
Research Design for Data Science | |
Data Science and Digital Transformation | |
Supervised Learning Methods | |
Unsupervised Learning Methods | |
Times Series Analysis and Forecasting | |
Python for Data Analysis | |
Data Engineering with Go | |
Foundations of Data Engineering | |
Data Science and Cloud Computing | |
Analytics Systems Engineering | |
Conversational AI Assistants | |
Data Pipelines and Stream Processing | |
Marketing Analytics | |
Financial Machine Learning | |
Web and Network Data Science | |
Natural Language Processing | |
Applied Probability and Simulation Modeling | |
Data Visualization | |
Sports Performance Analytics | |
Sports Management Analytics | |
Artificial Intelligence and Deep Learning | |
Knowledge Engineering | |
Computer Vision | |
Intelligent Systems and Robotics | |
Technology Entrepreneurship | |
Management Consulting | |
Project Management | |
Business Leadership and Communications | |
Special Topics in Data Science | |
Independent Study |
About the Final Project
As their final course in the program, students take either a master's thesis project in an independent study format or a classroom final project class in which students integrate the knowledge they have gained in the core curriculum in a team project approved by the instructor. In both cases, students are guided by faculty in exploring the body of knowledge of data science. The master’s thesis or capstone class project count as one unit of credit.
Course | Title |
---|---|
Choose one | |
Capstone Class | |
Thesis Research |