Master of Science in Computational Data Science

Data Science is concerned with extracting knowledge and insights from "big data" using theories and techniques that are drawn from computer science, mathematics, and statistics. Many innovations and developments result from the application of Data Science to domains such as biomedical sciences, physical sciences, geosciences, social sciences, engineering, security, defense, and education. Data Science provides information that is vital to making timely and strategic decisions in government and industry.

Temple's MS in Computational Data Science provides students with a strong foundation in algorithmic, computational, and statistical thinking, as well as a firm understanding of computer systems. These skills enable our students to analyze large quantities of data and discover new knowledge that can fuel new developments in many fields. Graduates of our program will be able to fill the increasing demand for data scientists, in industry, government, and education. They are also very well prepared for further graduate studies, research positions, or teaching careers.

If you are interested in getting an MS in Computational Data Science, but your undergraduate degree is in another field, click here tolearn how you can prepare to apply to this or any of our other MS programs. this or any of our other MS programs.

Course Requirements

To earn an MS in Computational Data Science, students take ten graduate courses (30 credits)1 as described below2.

      Four Required Core Courses

  • Machine Learning (CIS 5526)
  • Programming Techniques (CIS 5511)
  • Select One From:
    • Operating Systems (CIS 5512)
    • Principles of Data Management (CIS 5516)
    • Computer Architecture (CIS 5642)
  • Design and Analysis of Algorithms (CIS 5515) 

      Five Elective Courses

  • Data Analysis (at most 3 courses):
    • Data Mining (CIS 9664),
    • Modeling Social and Information Systems (CIS 5524),
    • Neural Computation (CIS 5525),
    • Probabilistic Graph Models (CIS 5535),
    • Text Mining and Language Processing (CIS 5538),
    • Computer Vision (CIS 5543),
    • Artificial Intelligence (CIS 5603)
  • Big Data (at most 3 courses):
    • Principles of Data Management (CIS 5516),
    • Advanced Topics in Data Base Systems (CIS 9665),
    • Operating Systems (CIS 5512),
    • Computer Architecture (CIS 5642),
    • Distributed Computing (CIS 5644),
    • Topics in Computer Science (CIS 5590), with approval, based on topic. For example, Emerging Storage Technologies, Data-Intensive and Cloud Computing
  • Domain Related (at most 2 courses, with approval):
    • For example, courses may be selected from Statistics, Biology, Genomics, Geology, GIS (Geographic Information Systems), Simulation/Modeling courses in Criminal Justice, Sociology, Econometrics, Mathematics, Public Health, Engineering, Biomedical Engineering,  
  • Preparatory Coursework (CIS 5000-5499, at most 1 course, with approval based on student's background)
  • Independent Study (CIS 9182/9282, at most one 3 credit course, with approved topic) registration form

      Master's Project

  1. All courses are three credits.
  2. Academic Standards. Students must have at least a 3.0 GPA in order to graduate. Students who receive more than two substandard grades (C+ or lower) are dismissed from the program.

Prerequisite Requirements

Before a student can apply to Temple's MS in Computational Data Science, they must have completed (or be registered in) the following prerequisite courses and/or have equivalent work experience.
  • Calculus I, II, and III (Mulitvariate Calculus), such as Math 1041, 1042, and 2043
  • Probability, such as Math 3031
  • Linear Algebra, such as Math 2103
  • Data Structures, such as CIS 2168
Prerequisite courses may be taken at Temple, as a non-matriculated student (through Continuing Studies, 215 204-2500), or at any accredited college. If you lack some of these requirements, click here to learn how you can prepare to apply(link is external) to this or any of our other MS programs.