Faculty advisors will help students determine their program of study. Courses starred with an asterisk * are currently unavailable online.
| CORE COURSES (18 credits) | |
| Students are required to take one course from each of the six categories below. The specific core courses taken will be determined in consultation with the student's faculty advisor. | |
| Data Processing Course (3 credits) — one of: | |
| CS 525 | ADVANCED DATABASE ORGANIZATION |
| CS 554 | DATA-INTENSIVE COMPUTING |
| CSP 554 | BIG DATA TECHNOLOGIES |
| Statistics Course (3 credits) — one of: | |
| MATH 563 | MATHEMATICAL STATISTICS* |
| MATH 564 | APPLIED STATISTICS |
| Machine Learning Course (3 credits) — one of: | |
| CS 584 | MACHINE LEARNING |
| MATH 569 | STATISTICAL LEARNING |
| Working with Data Course (3 credits): | |
| CSP/MATH 571 | DATA PREPARATION AND ANALYSIS |
| Project Management Course (3 credits): | |
| SCI 511 | PROJECT MANAGEMENT |
| Communication Course (3 credits): | |
| SCI 522 | PUBLIC ENGAGEMENT FOR SCIENTISTS |
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| ELECTIVE COURSES (9 credits) | |
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Students may choose 3 courses from the list below. These electives must be approved by the student’s faculty advisor. |
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| Computation Fundamentals | |
| CS 425 | DATABASE ORGANIZATION |
| CS 430 | INTRODUCTION TO ALGORITHMS |
| CS 450 | OPERATING SYSTEMS |
| CS 525 | ADVANCED DATABASE ORGANIZATION |
| CS 535 | DESIGN AND ANALYSIS OF ALGORITHMS |
| CS 546 | PARALLEL AND DISTRIBUTED PROCESSING |
| CS 553 | CLOUD COMPUTING |
| CS 554 | DATA-INTENSIVE COMPUTING |
| CS 589 | SOFTWARE TESTING AND ANALYSIS |
| Computer Science Applications | |
| CS 422 | DATA MINING |
| CS 512 | TOPICS IN COMPUTER VISION |
| CS 513 | GEOSPATIAL VISION AND VISUALIZATION* |
| CS 522 | ADVANCED DATA MINING |
| CS 529 | INFORMATION RETRIEVAL |
| CS 556 | CYBER-PHYSICAL SYSTEMS: LANGUAGES AND SYSTEMS |
| CS 557 | CYBER-PHYSICAL SYSTEMS: NETWORKING AND ALGORITHMS |
| CS 579 | ONLINE SOCIAL NETWORK ANALYSIS |
| CS 583 | PROBABILISTIC GRAPHICAL MODELS |
| CS 584 | MACHINE LEARNING |
| CS 585 | NATURAL LANGUAGE PROCESSING |
| Mathematics, Probability and Statistics | |
| MATH 454 | GRAPH THEORY AND APPLICATIONS* |
| MATH 486 | MATHEMATICAL MODELING I* |
| MATH 527 | MACHINE LEARNING IN FINANCE: FROM THEORY TO PRACTICE |
| MATH 532 | LINEAR ALGEBRA* |
| MATH 540 | PROBABILITY* |
| MATH 542 | STOCHASTIC PROCESSES* |
| MATH 553 | DISCRETE APPLIED MATHEMATICS I* |
| MATH 554 | DISCRETE APPLIED MATHEMATICS II* |
| MATH 565 | MONTE CARLO METHODS |
| MATH 567 | DESIGN OF EXPERIMENTS* |
| MATH 569 | STATISTICAL LEARNING |
| MATH 574 | BAYESIAN COMPUTATIONAL STATISTICS |
| Mathematical and Scientific Computing | |
| MATH 577 | COMPUTATIONAL MATHEMATICS I* |
| MATH 578 | COMPUTATIONAL MATHEMATICS II* |
| MATH 590 | MESHFREE METHODS* |
| BIOL 550 | BIOINFORMATICS AND BIOTECHNOLOGY* |
| PHYS 440 | COMPUTATIONAL PHYSICS* |
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| Required Capstone Course (6 credits) | |
| CSP 572 | PRACTICUM |
Other relevant 500-level coursework may be taken for elective credit, with approval of the program director.
Students must take a total of at least 9 credits of MATH coursework and at least 9 credits CS/CSP coursework to graduate, not including the capstone practicum course. Prerequisite courses MATH 474, CS 201, and CS 401, if taken, will not count towards degree fulfillment.
To provide students with the best overall educational experience, the preferred course of study is on Illinois Tech's Mies Campus. We also offer the program online for students who are working full-time in data-related fields, in the U.S. or Canada. Direct coordination between the program and students’ employers is essential for student success. Overseas students are encouraged to take recommended prerequisite courses online, then come to Chicago for the main course of study.