Data Science


The Master of Science in Computer Science (Data Science) provides students with a core background in Computer Science and specialized algorithmic, statistical, and systems expertise in acquiring, storing, accessing, analyzing and visualizing large, heterogeneous and real-time data associated with diverse real-world domains including energy, the environment, health, media, medicine, and transportation.

Total Units: 32

You must take the following required courses (12 units):

  • CSCI 570 – Analysis of Algorithms (4)
  • CSCI 585 – Database Systems (4)
  • CSCI 561 – Foundations of Artificial Intelligence (4)

Group Electives (3 course – minimum of 1 course from each of the two groups, 10-12 units):

Group 1 – Data Systems:

  • CSCI 548 – Information Integration on the Web (4)
  • CSCI 572 – Information Retrieval and Web Search Engines (4)
  • CSCI 586 – Database Systems Interoperability (4)
  • CSCI 587 – Geospatial Information Management (4)
  • CSCI 653 – High Performance Computing and Simulation (4)
  • CSCI 685 – Advanced Topics in Database Systems (4)
  • INF 551 – Foundations of Data Management (4)

Group 2 – Data Analysis:

  • CSCI 567 – Machine Learning (4)
  • CSCI 573 – Probabilistic Reasoning (3)
  • CSCI 686 – Advanced Big Data Analytics (4)
  • INF 553 – Foundations and Applications of Data Mining (4)
  • ISE 520 – Optimization: Theory and Algorithms (3)
  • MATH 467 – Theory and Computational Methods for Optimization (4)
  • MATH 574 – Applied Matrix Analysis (3)

Additional Electives (8-10 units)*:

  • Any 500 or 600 level course in CSCI (including additional group electives or special topics)
  • CSCI 590 – Directed Research (1-2, max 2)
  • CSCI 591 – Computer SCience Research Colloquium (1, max 2)
  • INF 554 – Informatin Visualization (4)
  • INF 558 – Building Knowledge Graphs (4)
  • MATH 458 – Numerical Methods (4)
  • MATH 501 – Numerical Analysis and Computation (3)
  • MATH 502A – Numerical Analysis (3)
  • MATH 502B – Numerical Analysis (3)
  • MATH 505A – Applied Probability (3)
  • MATH 601 – Optimization Theory and Techniques (3)
  • MATH 650 – Seminar in Statistical Consulting (3)

*Note: No more than 4 units may be taken at the 400-level, and maximum of 2 units of CSCI 590 and a maximum of 2 units of CSCI 591 may be applied.

A maximum of 3 INF courses can be taken toward the degree.

Thesis courses (CSCI 594a, CSCI 594b, CSCI 594z) and Internship courses (ENGR 595a, ENGR 595b, ENGR 595z) are not eligible for elective credit.

  • There is no examination required for the degree. 
  • A minimum grade point average of 3.00 must be earned on all course work applied toward the M.S. degree and all graduate course work taken at USC.
  • A maximum of 4 units may be taken from approved 400-level courses in either Electrical Engineering or Computer Science; the remaining units must be approved courses at the 500 or 600 level.
  • Prerequisites must be taken prior to an advanced course. Even if a prerequisite is waived, you may not take the prerequisite course AFTER taking the advanced course.
  • Internship and Thesis credits cannot count as elective units toward the degree.
  • CSCI 590 Directed Research is a variable unit course, and can be taken for one or two units. A maximum of two units can apply toward the degree.
  • CSCI 591 Research Colloquium can be taken a maximum of two times for one unit each.
  • Availability of courses per semester may occasionally change.