MS in Data Science

The Master of Science in Data Science is designed to meet the rising demand for highly skilled data science and data analytics professionals.  It prepares students for careers in data science and analytics with a broad knowledge of the required tools, techniques, and methods. The program focuses on relevant areas including statistical analysis, natural language processing, computational linguistics, information retrieval, information visualization, social network analysis, text analytics and data mining. The program helps graduates to acquire the types of skills and competencies needed in designing, implementing and transforming data sets and large volumes of information into actionable knowledge. It provides students with the knowledge they need to manage data science and data analytics projects and work with analytics tools and technologies. The program aimed at educating a new generation of information professionals capable of taking the leadership role through connecting the dots and using data to support strategic initiatives within the organization.

 

DEGREE STRUCTURE

FOUNDATION COURSES (12 Hours):

The core courses are designed to cover the basic concepts and foundational knowledge. Students must complete the following four core courses:

 

INFO 5501

Fundamentals of Data Science and Data Analytics

INFO 5502

Analytic Tools, Techniques and Methods

INFO 5709

Data Visualization and Communication

INFO 5090/5082

Practicum and Field Study/Research Seminar

 

GUIDED ELECTIVES (15 hours):

The guided electives are the courses with advanced topics in data Science and data analytics.

Students must take 15 hours from the following list of courses. 

 

CSCE 5300

Introduction to Big Data and Data Science

INFO 5810

Data Analysis and Knowledge Discovery

DSCI 5240

Data Mining

DSCI 5330

Enterprise Applications of Business Intelligence

DSCI 5340

Predictive Analytics and Business Forecasting

INFO 5503

Knowledge Management Processes and Practices

DSCI 5360

Data Visualization for Analytics

INFO 5307 

Knowledge Management Tools and Technologies

INFO 5737

Information and Cyber-Security 

LING 5360

Semantic Ontologies

 

GENERAL ELECTIVES (9 hours):

Students must take 9 hours from the following list of courses. They are allowed to pursue courses from outside this list and in their areas of interest with the approval of the advisor.

 

  • INFO 5731 Computational Methods for Information Systems
  • INFO 5737 Information and Cyber-Security 
  • ATPI 5320 Contemporary Issues
  • INFO 5707 Data Modeling and Data Design
  • INFO 5735 Usability & User Experience Assessment 
  • INFO 6880 Health Research Methodology
  • LING 5530 Semantics and Pragmatics
  • LING 5550 Corpus Linguistics
  • LING 5560 Discourse Analysis
  • LTEC 5300 Learning and Cognition
  • LING 5410 Computational Linguistics
  • LING 5360/LING 6130 Natural Language Processing
  • LING 5360/LING 6060 Data Analysis in Human Language Technology I
  • LING 5360/LING 6140 Data Analysis in Human Language Technology II