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.

Note:  In addition to fulfilling general requirements for the MSDS degree, students in Analytics Management must take two specialization core courses: MSDS 474-DL Accounting and Finance for Technology Managers and one of three courses selected from MSDS 475-DL Project Management, MSDS 480-DL Business Leadership and Communications, or MSDS 485-DL Data Governance, Ethics, and Law.


Core Courses (8 units)

Course Title
MSDS 400-DLMath For Data Scientists
MSDS 401-DLApplied Statistics with R
MSDS 402-DLData Science and Research Practice 1
or MSDS 403-DL Data Science and Digital Transformation
MSDS 420-DLDatabase Systems and Data Preparation
MSDS 422-DLPractical Machine Learning
MSDS 460-DLDecision Analytics
MSDS 475-DLProject Management
or MSDS 480-DL Business Leadership and Communications
or MSDS 485-DL Data Governance, Ethics, and Law
MSDS 498-DLCapstone Class
or MSDS 590-DL Thesis Research

Which course should students take?

  • Students without a background in data science should select MSDS 402-DL Data Science and Research Practice
  • Students with a background in data science should select MSDS 403-DL Data Science and Digital Transformation.  Students who have at least two years’ experience in the field and have or had a title, such as data scientist, data analyst, statistician, data engineer, business analyst, etc. should select this course.

Specialization Courses (4 units)

Course Title
MSDS 474-DLAccounting and Finance for Technology Managers
MSDS 475-DLProject Management 1
or MSDS 480-DL Business Leadership and Communications
or MSDS 485-DL Data Governance, Ethics, and Law
Any two electives
Supervised Learning Methods
Unsupervised Learning Methods
Times Series Analysis and Forecasting
Python for Data Analysis
Data Engineering with Go
Foundations for Data Engineering
Analytics Application Engineering
Analytics Systems Engineering
Real-Time Interactive Processing and Analytics
Real-Time Stream Processing and Analytics
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
Business Process Analytics
Data Governance, Ethics, and Law
Special Topics in Data Science
Independent Study

Complete two of these three courses:  one to fulfill the core requirement and one to fulfill the specialization requirement.

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