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Department of Computer Science College of Arts and Sciences

M.S. in Data Science (MSDS) Requirements

General Requirements

All MSDS students must take 30 credit hours in order to graduate. There are four required courses:

  • CS 510: Database Application Development or CS 610: Database Systems
  • CS 652: Advanced Algorithms and Applications
  • CS 667: Machine Learning
  • CS 685: Foundation of Data Science or CS 680: Matrix Algorithms for Data Science

Program electives include other CS graduate courses such as big data computing, data mining, natural language processing, deep learning, data visualization, high-performance computing and computer security courses, and approved non-CS electives such as business intelligence, quantitative analysis for business managers, bioinformatics, biostatistics, and graduate level statistical analysis courses. Course descriptions are available in the UAB Graduate Catalog. The program is defined in terms of either of two plans:

  • Plan I: 24 credit hours of courses and 6 credit hours of thesis research (CS 699: Master's Thesis Research). Among the 24 course credit hours, at least 15 of them must be CS graduate courses.
  • Plan II: 30 credit hours of courses (course work only; does not require a thesis), among which at least 21 credit hours must be CS graduate courses.

Most students choose the Plan II option. Plan I contains a significant research component and requires the student work closely with a faculty member on a research project. This project should be begun early in the program.

Suggested Study Plan

Four core courses and six electives are required. Electives can be any CS graduate courses, some of which can be taken from the following lists of courses, grouped by fields.

PLEASE NOTE: No more than three 500-level courses (9 credit hours) can count toward the MSDS degree. At most, three (3) credit hours combined of special courses (CS 598: Practical Work Experience and/or CS 697: Directed Readings) can count towards the MSDS degree. Be aware that required courses may change; please consult the graduate program director at csgradprogram@uab.edu for specific requirements.

Data Analytics

  • CS 616: Big Data Programming
  • CS 660: Artificial Intelligence
  • CS 662: Natural Language Processing
  • CS 663: Data Mining
  • CS 665: Deep Learning
  • CS 673: Computer Vision and Convolutional Neural Networks
  • CS 675: Data Visualization
  • CS 680: Matrix Algorithms for Data Science
  • CS 687: Complex Networks

Cyber Security

  • CS 623: Network Security
  • CS 636: Computer Security
  • CS 643: Cloud Security
  • CS 645: Modern Cryptography
  • CS 689: Cyber Risk Management

High Performance Computing

  • CS 632: Parallel Computing
  • CS 633: Cloud Computing

Non-CS Electives

Students may take up to three (9 credit hours) non-CS electives from the following list of courses, upon the approval of the graduate program director:

  • Business Intelligence
    • MBA 610: Business Analytics and AI
    • MBA 658: Applied Marketing Research
    • MBA 662: Quantitative Analysis for Business Managers
  • Bioinformatics
    • INFO: 601 Introduction to Bioinformatics
    • INFO: 602 Algorithms in Bioinformatics
    • INFO: 603 Biological Data Management
  • Biostatistics
    • BST 611: Intermediate Statistical Analysis I or BST 621: Statistical Methods I
    • BST 612: Intermediate Statistical Analysis II or BST 622: Statistical Methods II

    • PLEASE NOTE: You may not apply both BST 611 and BST 621 to the MSDS degree due to the amount of content overlap between the two courses; similarly, you may not apply both BST 612 and BST 622 to the MSDS degree.

Plan I (Thesis Option) Guidance

If you are interested in Plan I (Thesis Option) for your MSDS, you must maintain good academic standing and contact a faculty advisor who agrees to serve as your MS thesis advisor/mentor. Refer to Graduate School's thesis and dissertations page for the steps to completing your thesis, beginning with forming your committee.