About the Program
The M.S. in Data Science and Analytics offers advanced practical training for in-demand modern skills to manipulate, organize and present data essential for informed, evidence-based decision-making and planning across industries. This program is open to students with basic programming and statistical skills from all undergraduate majors. Courses cover highly marketable techniques using data analytics tools, computer coding, machine learning, geospatial programming, data design, visualization, and analysis. Students will develop professional skills in project management, communications, data governance, and creative problem-solving for effective collaboration. Unique components of the program include workshops with local experts and an applied-skills internship with industry partners.
About the Data Science and Analytics Interdisciplinary Unit
dataanalytics.buffalostate.edu/
Joaquin Carbonara, Coordinator
Mathematics Department
Science and Mathematics Complex 379
(716) 878-6423
Admission Requirements
1. A bachelor’s degree from an accredited college or university with a minimum cumulative GPA of 2.5 (4.0 scale).
2. A two- to three-page statement of intent (essay) that includes the following:
- educational and professional objectives; and
- an explanation of the reasons for interest in data science and analytics
3. An interview with the program coordinator or a DSA faculty member. The student will be contacted for an appointment after the completed application is received.
In addition, all applicants must review the Admission to a Graduate Program section in this catalog.
Learning Outcomes
Students will:
1. select and apply an appropriate statistical, mathematical or computational model for a given quandary
2. acquire data from data scraping and open sources and understand the ethical and legal ramifications of data acquisition
3. store, clean, organize, and manipulate real world data from multiple sources
4. compose and present an effective oral, written report or dynamic dashboard, to a lay audience (including storytelling and data visualization) that enhances the audience’s understanding and reveals properties of the data
5. use the appropriate software or programming application (Python, SQL, SAS, SPSS, Excel) to manage and analyze data
6. perform effectively as a member of a team to execute a project and will understand what contributes to team success
7. integrate context specific information into their data manipulation allowing them the flexibility to interpret data from many different environments
Program Requirements
Required Courses (18 credit hours)
Complete ALL of the following Courses:
CIS512 INTRODUCTION TO DATA SCIENCE AND ANALYTICS | 3 - Credit Hours
DSA501 DATA ORIENTED COMPUTING AND ANALYTICS | 3 - Credit Hours
OR DSA601 MACHINE LEARNING MODELS IN PYTHON | 3 - Credit Hours
DSA688 EXPERIENTIAL LEARNING IN DATA SCIENCE AND ANALYTICS | 3 - Credit Hours
MAT616 ELEMENTS OF MATHEMATICS, PROGRAMMING AND COMPUTER SCIENCE FOR DATA SCIENCE | 3 - Credit Hours
PSM601 PROJECT MANAGEMENT FOR MATH AND SCIENCE PROFESSIONALS | 3 - Credit Hours
OR PSM602 COMMUNICATION STRATEGIES FOR MATH AND SCIENCE PROFESSIONALS | 3 - Credit Hours
OR DSA650 DATA STRATEGY AND GOVERNANCE | 3 - Credit Hours
MAT646 INTRODUCTION TO STATISTICS FOR DATA SCIENCE | 3 - Credit Hours
OR BIO670 BIOLOGICAL DATA ANALYSIS | 3 - Credit Hours
Selection of one of the above "Plus Courses" (3 credit hours) PSM601, PSM602, or DSA650
Selection of one of the above statistics courses (3 credits) MAT646 or BIO670
Elective Courses (12 credit hours)
Choose four courses by advisement from the following (each course is 3 credit hours) or additional courses by advisement
Earn at least 12 credits from the following:
BUS519 COMMUNICATION FOR LEADERS AND MANAGERS | 3 - Credit Hours
COM547 DATA ANALYTICS FOR STRATEGIC COMMUNICATION | 3 - Credit Hours
DSA501 DATA ORIENTED COMPUTING AND ANALYTICS | 3 - Credit Hours
DSA601 MACHINE LEARNING MODELS IN PYTHON | 3 - Credit Hours
DSA610 DATABASES AND THE DATA SCIENCE INFORMATION LIFE CYCLE | 3 - Credit Hours
DSA621 DATA SCIENCE TOOLS IN ENERGY ENGINEERING | 3 - Credit Hours
DSA652 APPLIED TIME SERIES ANALYSIS IN BANKING RISK MANAGEMENT | 1 - Credit Hours
ENT581 RENEWABLE DISTRIBUTED GENERATIONAND STORAGE | 3 - Credit Hours
ENT582 SMART GRID FROM SYSTEMS PERSPECTIVE | 3 - Credit Hours
ENT622 MACHINE LEARNING FOR MATERIALS SCIENCE IN CLEAN ENERGY | 3 - Credit Hours
GEG584 GEOSPATIAL PROGRAMMING | 3 - Credit Hours
GEG585 INTERACTIVE AND WEB-BASED MAPPING | 3 - Credit Hours
HEA730 DATA VISUALIZATION AND STORYTELLING | 3 - Credit Hours
PSM601 PROJECT MANAGEMENT FOR MATH AND SCIENCE PROFESSIONALS | 3 - Credit Hours
PSM602 COMMUNICATION STRATEGIES FOR MATH AND SCIENCE PROFESSIONALS | 3 - Credit Hours
SPF689 METHODS AND TECHNIQUES OF EDUCATIONAL RESEARCH | 3 - Credit Hours
PSM602 - COMMUNICATION STRATEGIES FOR MATH AND SCIENCE PROFESSIONALS (This course cannot count for both a "plus" and elective)
30 Total Credit Hours