Subscribe to DSC Newsletter

The Master of Science in Data Science (MSDS) is an 11‐month professional masters program, designed to meet the increasingly data‐intensive needs of industry and government. The program starts near the beginning of July and ends the next year in mid-May. Core program courses will be taught by faculty from the Departments of Computer Science, Statistics, and Systems and Information Engineering.

Three key features of this program are (a) an integrated curriculum and data experience; (b) the compressed duration; and (c) a cohort experience. To achieve these, the curriculum is tightly prescribed with about 80% common to all students. The curriculum is integrated across courses, with several large complicated data sets woven across courses to increase program cohesion. The compressed duration is designed to minimize the time from start to finish, and the cohort experience will allow students to consistently work together in teams. At the conclusion of the program the students will address an important data science challenge through a capstone experience. Students will commence this work with a proposal describing their objectives. In conducting this final exercise students will be guided, mentored, and eventually evaluated by faculty members from the different disciplines.

Prerequisites

Applicants need to have a completed undergraduate degree in hand by the start of the program, but the specific undergraduate major is not important. However, there is prerequisite knowledge needed for the MSDS program:

  • Single variable calculus (similar to UVA MATH 1210-1220 or MATH 1310-1320 or APMA 1090-1110)
  • Linear algebra or matrix algebra (similar to UVA MATH 3350 or MATH 3351 or APMA 3080)
  • An introductory statistics course (similar to UVA STAT 2120)
  • An introductory programming course (similar to UVA CS 1110 or CS 1111 or CS 1112)

There are many other ways to acquire the prerequisite knowledge. For instance, you may be able to take needed courses during the UVA summer session, or at some other school, or even via a MOOC. We are happy to work with students, so if you have any questions about your background just ask the MSDS program director for an assessment.

Curriculum

Course requirements for the MSDS program:

Summer Term (6 weeks, starting approximately July 1)
      CS 5014: Computation for Data Science
      STAT 6010: Statistical Computing and Data Visualization

Fall Term
      STAT 6021: Linear Models for Data Science
      CS 5161: Design and Analysis of Algorithms for Data Science
      DS 6001: Topics in the Practice of Data Science
      Elective

January Term
      DS 6002: Ethics of Big Data

Spring Term
      SYS 6018: Applied Data Mining
      SYS 6016: Machine Learning
      DS 6003: Capstone Project
      Elective

Selection of elective courses is done in consultation with the program director. There are a variety of possible electives available, including the following:

Fall Term
      CS 6444: Introduction to Parallel and Cloud Computing
      SYS 6035: Agent‐Based Modeling & Simulation
      STAT 5260: Categorical Data Analysis
      STAT 5140: Survival Analysis & Reliability Theory
      SYS 6043: Applied Optimization
      SYS 6044: Applied Probability

Spring Term
      CS 6750: Database Systems
      STAT 5170: Applied Time Series
      STAT 5340: Bootstrap and Other Resampling Methods
      MATH 5110: Stochastic Processes

Other electives are possible, depending on available courses.

How To Apply

The MSDS program is hosted by the Department of Statistics, and is a concentration within the MS in Statistics program. A complete application consists of the following:

  • Completed application form
  • Statement of purpose
  • GRE scores (general exam only)
  • TOEFL scores (not required for students who obtained a degree from an institution where English is the primary language of instruction)
  • Transcripts
  • Two letters of recommendation

Note: Contact program director Jeff Holt by March 31 for information on how to submit application materials. (International students should apply as soon as possible to allow time to process visa applications.)

Note on GRE and TOEFL scores: It is fine if the official scores arrive after you apply. If you have unofficial scores, report them in the "score self-report" part in the application system.

Note to UVA students: In some cases, the GRE requirement can be waived. Contact the program director for details.

Contact

Questions about the program or application process can be directed to the program director at [email protected].

For more details, visit http://dsi.virginia.edu/academics

Views: 1298

Follow Us

On Data Science Central

On DataViz

On Hadoop

© 2017   AnalyticBridge.com is a subsidiary and dedicated channel of Data Science Central LLC   Powered by

Badges  |  Report an Issue  |  Terms of Service