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Degree Requirements

Course Number and TitleCredits
Total68
COMPUT 601 – Introduction to Graduate Studies1
Required Core Courses
CS 533 – Introduction to Data Science
CS 534 – Machine Learning
MATH 562 – Probability and Statistics II
MATH 572 – Computational Statistics

12
Data Science Elective Courses
3 credits must be in CS and 3 must be in MATH.
Pre-approved data science electives can be found in the student handbook
6
Elective Courses
Must be approved by the supervisory committee and Computing Program directors.
Pre-approved electives and specific requirements are given in the student handbook.
15
COMPUT 691 Doctoral Comprehensive Examination1
COMPUT 693 Dissertation33

Data Science Degree Flow Chart 2018-2019 (PDF)

Pre-approved Data Science Elective Courses

Data Science Electives in Computer Science

  • CS 510 Databases
  • CS 535 Large-scale Data Processing and Analysis
  • CS 536 Natural Language Processing
  • CS 573 Introduction to Information Retrieval
  • CS 538 Recommender Systems for Online Personalization
  • CS 539 Social Media Mining
  • CS 557 Artificial Intelligence
  • CS 633 Deep Learning
  • CS 637 Advanced Topics in Information Retrieval

Data Science Electives in Math

  • MATH 503 Linear Algebra
  • MATH 515 Real and Linear Analysis
  • MATH 527 Introduction to Applied Math for Scientists and Engineers
  • MATH 566 Numerical Methods I Numerical Methods II
  • MATH 571 Data Analysis
  • MATH 573 Time Series Analysis
  • MATH 574 Linear Models

Pre-approved Additional  Electives by Focus Area

Anthropology

  • ANTH 504 Statistical Methods in Anthropology

Biometry

  • BIOL 601 Biometry
  • BIOL 603 Advanced Biometry

Ecology, Evolution and Behavior

  • EEB 607 Quantitative Methods for Population and Habitat
  • EEB 621 Advanced Ecological Data Analysis

Econometrics

  • ECON 521 Mathematical Statistics and Introduction to Advanced Econometrics
  • ECON 522 Advanced Econometrics

Electrical Engineering

  • ECE 556 Pattern Recognition and Machine Learning

Geoscience

  • GEOS 505 Introduction to Numerical Methods for the Geosciences
  • GEOS 661 Advanced Image Processing

Geostatistics

  • GEOPH 522 Data Analysis and Geostatistics
  • GEOPH 575 Geophysical Applications of Digital Signal Processing

Hydrology and Hydrogeology

  • CE 630 Vadose Zone Hydrology
  • CE 633 Contaminant Hydrology

Materials Science

  • MSE 563 Materials Modeling