Masters in Data Science

 

This is an interdisciplinary Master of Science program offered jointly by the Department of Statistics (COAS) and the Department of Computer Science (CEAS), housed in the Department of Statistics. Data Science is today one of the most rapidly developing disciplines and data scientists are in high demand in the job market. Students in this program would develop a skill set that will allow them to take on current and future complex data challenges. Graduates will be able to store and access data from a variety of sources (also heterogeneous), process Big Data architecture, apply analytic techniques and algorithms (including statistical and data mining) to large, complex data sets, apply relevant environments for data processing and visualization, work in collaborative teams and communicate effectively.

A minimum of 35 credits is required and the resulting degree is a Master of Science in Data Science.

Admission requirements

  • Undergraduate program that includes calculus and linear algebra
  • A course in probability
  • A course in statistical methods
  • Strong background in an object oriented programming language such as Java or C++

Application

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Required and Elective Courses

Semester 1 (Fall)

  • STAT 6620 - Applied Linear Models  (3 hours)
  • STAT 5870 - Big Data Analysis Using Python  (3 hours)
  • CS 6100 - Advanced Storage, Retrieval and Processing of Big Data (3 hours)

Semester 2 (Spring)

  • STAT 5860 - Computer Based Data Analysis (3 hours)
  • CS 5610 - Advanced R Programming for Data Science (4 hours)
  • CS 5821 - Machine Learning (3 hours)

Semester 3 (Fall)

  • STAT 6800 - SAS Programming (3 hours)
  • CS 5430 - Database Systems (3 hours)
  • And MS Project 1

        STAT 6970 - Data Science Masters Project (4 hours)
          or
        CS 6970 - Master's Project (2 to 6 hours)

Semester 4 (Spring)

  • STAT Elective chosen from List 1 below (3 hours)
  • CS Elective chosen from List 2 below (3 hours)
  • And MS Project 2

        STAT 6970 - Data Science Masters Project (4 hours)
          or
        CS 6970 - Master's Project (2 to 6 hours)

List 1 - STAT Electives

  • STAT 5610 - Applied Multivariate Statistical Methods  (3 hours)
  • STAT 5630 - Sample Survey Methods (3 hours)
  • STAT 5660 - Nonparametric Statistical Methods  (3 hours)
  • STAT 5820 - Time Series Analysis  (3 hours)
  • STAT 6500 - Statistical Theory I (4 hours)
  • STAT 6600 - Statistical Theory II (4 hours)
  • STAT 6640 - Applied Mixed Models (3 hours)
  • STAT 6650 - Advanced Statistical Inference (3 hours)

List 2 - CS Electives

  • CS 5260 - Parallel Computations (3 hours)
  • CS 5300 - Artificial Neural Systems (3 hours)
  • CS 5310 - Algorithms (3 hours)
  • CS 5560 - Network Programming (3 hours)
  • CS 6260 - Advanced Parallel Computations (3 hours)
  • CS 6430 - Database Management System Implementation (3 hours)
  • CS 6530 - Data Mining (3 hours)