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MS In Data Science Degree Requirements

The MS in Data Science program, offered jointly by the Department of Computer & Information Science in the College of Engineering and the Department of Mathematics in the College of Arts & Sciences, provides advanced education to prepare students for professional positions in data analysis, informatics, data-driven decision-making, and related fields.

You'll gain a strong foundation in information theory, mathematics and computer science with current methodologies and tools to enable data-driven discovery, problem-solving, and decision-making.

Are you a current student or academic advisor? Please see the bottom of this page for Frequently Asked Questions and an advising tips sheet. 

Graduate program curriculum outline

Students in the MS in Data Science program must complete a total of 30 credits via a combination of required and elective courses. More detailed information about required courses and electives can be found below. 

Major Required (Core) Courses (Total # of courses required = 5)

Please use the Graduate Course Catalog to view course descriptions.

Course Number Course Title Credit Hours

MTH 522

Mathematical Statistics


CIS 552**

Database Design


DSC 520/EAS 520

Computational Methods


DSC 530/CIS 568
CIS 530/DSC 531
Data Visualization Workshop
Advanced Data Mining

DSC 550 


DSC 550 and DSC 690

Master's Project


Data Science Thesis




Subtotal # Core Credits Required

15 (thesis = 18)

Technical Elective Course Choices (Total courses required = 5)


Data Science Technical Elective



Data Science Technical Elective



Data Science Technical Elective



Data Science Technical Elective



Data Science Technical Elective*

3 (thesis=0)


Subtotal # Elective Credits Required

15 (thesis=12)

*Students doing a thesis are required to either register for (i) DSC 550 (3 credits) followed by DSC 690 (3 credits), or (ii) DSC 690 (6 credits)

**CIS 452 may be substituted for CIS 552 if you have not taken an undergraduate database course before

Curriculum summary

Total number of courses required for the degree


Total credit hours required for degree


MS in Data Science required courses

Please use the Graduate Course Catalog to view course descriptions.

  • MTH 522 - Mathematical Statistics (3 credits)
  • CIS 552 - Database Design (3 credits) or CIS 452 - Database Systems (3 credits)
    • Note: If you have taken an undergraduate database course before you should take CIS 552.
    • Note:  Students cannot take both CIS 452 and CIS 552.
  • DSC 520/EAS 520 - Computational Methods (3 credits) 
  • DSC 530/CIS 568 - Data Visualization (3 credits) OR DSC 531/ CIS 530 - Advanced Data Mining (3 credits)
    • Note: If you take both DSC 530 and DSC 521/CIS 530 then one of the courses will count as a technical elective.
  • DSC 550 - Master's Project (3 credits)

MS in Data Science technical electives

All graduate-level (500+) computer science (CIS), math (MTH), and data science (DSC) courses count as data science technical electives. Students may also take any approved 400-level MTH, DSC, or CIS course provided (i) The student has not taken any course similar in undergraduate, (ii) the 500-level course on the same topic has not been taken yet. Note that at most two 400-level courses can be counted towards the degree. Note that for 400-level courses, your transcript might temporarily say "No Credit Earned & Include in GPA". After the semester is over, assuming you have a passing grade in the class, please email one of the data science co-directors or your academic advisor (listed in COIN) to have this converted to "Credit Earned".

Below we provide a list of technical elective courses that are regularly offered through computer science, mathematics, and data science. 

Please use the Graduate Course Catalog to view course descriptions.

  • DSC 690 - Data Science Thesis (3 credits)
  • MTH 463 - Math Modeling (3 credits)
  • MTH 440/540 - Mathematical and Computational Consulting (3 credits)
  • MTH 465/565 - Small World Networks (3 credits)
  • MTH 472/572 - Numerical Methods for Partial Differential Equations (3 credits)
  • MTH 473/573 - Numerical Linear Algebra (3 credits)
  • MTH 474/574 - Numerical Optimization (3 credits)
  • MTH 475/575 - Advanced Numerical Methods for PDEs(3 credits)
  • MTH 595 - Independent Study (3 credits)
  • MTH 599 - Special Topics (3 credits)
  • CIS 412 - Artificial Intelligence (3 credits)
  • CIS 430 – Data Mining and Knowledge Discovery (3 credits)
  • CIS 431 - Human and Computer Interaction (4 credits)
  • CIS 454 - Computer Graphics (3 credits)
  • CIS 455 - Bioinformatics (3 credits)
  • CIS 467 - Image Analysis and Processing (3 credits)
  • CIS 490 - Machine Learning (3 credits)
  • CIS 522 - Algorithms & Complexity (3 credits)
  • CIS 550 - Advanced Machine Learning (3 credits)
  • CIS 554 - Advanced Computer Graphics (3 credits)
  • CIS 555 - Advanced Bioinformatics (3 credits)
  • CIS 556 - Gamification Design (3 credits)
  • CIS 561 - Artificial Intelligence (3 credits)
  • CIS 563 - MultiAgent Systems (3 credits)
  • CIS 569 - Visual Analytics (3 credits)
  • CIS 581 - Design and Verification of Information Systems (3 credits)
  • CIS 585 - Image Processing and Machine Vision (3 credits)
  • CIS 595 - Independent Study (3 credits)
  • CIS 602 - Pattern Analysis (3 credits)
    • Note: CIS 602 is a special topics course. Only Pattern Analysis is approved as an elective.
  • CIS 602 - Human-Computer Interaction (3 credits)
    • Note: CIS 602 is a special topics course. Only  Human-Computer Interaction is approved as an elective.
  • CIS 602 - Computer Vision (3 credits)
    • Note: CIS 602 is a special topics course. Only computer vision is approved as an elective.

In addition to computer science (CIS), math (MTH), and data science (DSC) technical electives, students can take approved technical electives from the list of courses below. 

Please use the Graduate Course Catalog to view course descriptions.

  • AXD 446 - Virtual Reality Design (3 credits)
    • Note: AXD 446 is a special topics course. Only Virtual Reality Design is approved as an elective.
  • CEN 530/MAR 599 - Introduction To Geographical Information Systems (3 credits)
  • EAS 502 - Numerical Methods (3 credits)
  • EAS 621/622 - Mathematical and Computational Consulting / Scientific Computational Research Seminar (3 credits)
  • ECE 520 - Wireless Networks and Mobile Security (3 credits)
  • ECE 548 - Cyber Threats and Security Management (3 credits)
  • ECE 549 Network Security (3 credits)
    • Note: Enrollment with permission of instructor only
  • EGR 500 - Internship (1 to 3 credits); see here
    • Note: Curricular Practical Training (CPT). The US government's rules are that CPT must be a part of your educational experience. As such, the internship must be relevant to your field of study and contribute to your degree. For example, if you have already taken 30 credits, or other required coursework will put you at 30 credits, EGR 500 cannot be taken.
    • Note: The College of Engineering will only approve internships (through EGR 500) if (i) the internship is paid at a reasonable rate and (ii) for 3 credits over the fall/spring students are expected to work for at least 20 hours/week. For the summer the internship should be fulltime.
  • MAR 536 - Biological Statistics II (3 credits)
  • MAR 580 - Special Topics
    • FVCOM: Algorithms and Training (3 credits)
    • Note: this class might also show up as MAR 599 in COIN
  • MIS 432 - Business Data Systems (3 credits)
  • MIS 433 - Advanced Database E-Business Applications Development (3 credits)
  • MIS 670 - Managing Information (3 credits)
  • MIS 674 -  Applied Business Analytics & Information Visualization (3 credits)
  • MIS 681 - Business Intelligence and Knowledge Management (3 credits)
  • MKT 671 - Marketing Research (3 credits)
  • POM 500 - Statistical Analysis (3 credits)
    • Note:  POM 500 may be designated as an Online and Continuing Education (OCE) course. Students can enroll in the OCE version of the course and get credit towards the masters degree.
  • POM 681 - Business Analytics and Data Mining (3 credits)
  • PSY 502 - Statistical Methods in Psychology (3 credits)

Advising tips for advisors and students

The complete set of University Policies can be found in the graduate catalog. Below we list the most important policies for academic advising.

  1. Full-time students take 3 courses (9 credits) per semester. Students considering to overload (> 9 credits) or part-time (<9 credits) should discuss with their academic advisor.
  2. No more than 12 credits are allowed per semester
  3. International students must be registered for 9 credits to satisfy visa requirements.
  4. If you don't need 9 credits (typically the last semester), international students must fill out a reduced course-load form found on the ISSC website
  5. If you take a graduate level class (500 or higher), you need to earn a C or better for the course to count
  6. You can take up to 6 credits of undergraduate senior level (400 or higher) coursework. You need to earn a B or better for the course to count
  7. Students may take up to three courses through the Office of Online and Continuing Education (OCE) during their entire MS program

Important Notes

If you started the program before Spring 2020, the following policy applies to you: DSC 530 will not be offered over the next year. As a result, the following policy is in effect: DSC masters students can take either CIS430/530 (data Mining) or CIS 550 (Advanced Machine Learning) to satisfy the DSC 530 (data visualization) core course requirement. Note that students are also required to take a course in Database Design (CIS 452/552). Students who have taken an undergraduate course in databases are allowed to take CIS 530 to satisfy their database requirements. In such cases, the student must take CIS 550 to satisfy the data visualization requirement.

As many as two undergraduate electives (6 credits) may serve as graduate electives. This includes the courses CIS430 and CIS 452 that are mentioned above

Frequently asked questions

Projects must be completed under the supervision of a DSC faculty member, and students must enroll in DSC 550 (Master's Project). Typically, there will be one instructor per student. But there could be multiple students assigned to a faculty member in the form of a group project -- its up to your project mentor to decide this, and it ultimately up to them to determine if you have completed the project.

You can do an internship and DSC 550 (Master's Project) concurrently. An internship could in principle be "substituted" for the Master's Project, but this would have to be arranged by your project faculty mentor. In particular, you would still need to register for DSC 550 under the direction of a DSC faculty member. If would be up to you, the faculty mentor, and the internship to define the scope of the project and how it would be carried out. If you are an international student and need an CPT for internship work, you cannot perform any internship work as part of DSC 550. Instead you should enroll in EGR 500.

All students are required to engage in a capstone experience.

The Master's Project typically takes 1 semester (3 credits) and a master's thesis typically takes 2 semesters (6 credits; 6 credits is required to graduate with a thesis option). The thesis will require that you write a thesis and defend it to a committee of three faculty members of your choosing as part of a public talk. The Master's Project also requires you to give a talk, but there's no thesis or committee defense. Typically, the thesis option is intended for students who either may be considering pursuing a Ph.D. or are interested in academic research projects. 

In both cases, the first step is to find a research advisor. You should look over the list of data science faculty members and find someone whose interests match yours. The best way to survey research interests is to look over faculty profiles or the CSCVR research groups page. Students are required to find their advisor at least 2 months before the start of DSC 550.

Once you and your advisor have settled on a project, ask your advisor to have the registrar open a section of either DSC 550 (Master's Project) or DSC 690 (Master’s Thesis) under them and then you will need to enroll into that specific section of the course being taught by your advisor. Students interested in a thesis must enroll in DSC 550 for the first semester of project work, then DSC 690 in the following semester.

Students may take up to three online courses during their entire MS program. Courses designated "online" are those offered through the Online and Continuing Education (OCE) program. 

Online courses offered through the Online and Continuing Education (OCE) program may require that you fill out the Current Student Registration Request - COIN Error Received Form found here.

Congratulations on your internship offer! To get a CPT you must be enrolled in a CPT-approved course. A CPT can only be issued for EGR 500, and only 3-credits can be accrued for EGR 500. If you've already taken 3 credits of EGR 500, unfortunately you cannot get a CPT. However, you may be able to engage with an industry-driven project through MTH 540.

Graduate students who need to be considered full time (e.g. for health insurance or visa purposes) have to complete the full-time status form; Grad Studies and the Registrar will process it. All international students (undergrad or grad) who are not enrolled full time also have to submit a completed reduced course load form via ISSC's webpage. Sometimes there's overlap: an international student with an assistantship who is enrolled part time would need to complete both forms. 

Congratulations on finishing the program! You should be on the lookout for an email from the registrar for instructions on applying to graduate. You should also fill out the DS Master’s Check Sheet form (DS course checklist for graduates) and send it to one of the program co-directors. This form will list all 10 classes you intend to use towards your MS degree. Students enrolled in the accelerated BS/MS program should denote which classes were also used towards the BS degree (up to 9 credits can be double-counted towards both the BS and MS). 

International students can take at most 1 online class per semester during the academic year. During the summer students can take 2 online classes. 

These rules change if you are in your final semester, in this case:

3 classes left: student can take 1 online,  2 face-to-face

2 classes left: student can take 1 online, 1 face-to-face – Student needs to file for RCL application to ISSC

1 classes left: student must take this class face-to-face – Student needs to file for RCL application to ISSC

If you are completing your degree over the summer or winter, you must take at least one face-to-face class.

Depending on the kind of error, it might be most efficient to contact either the instructor or the data science help desk (

Here are some common errors:

CIS-OGP OR OGC only: Data science students are allowed to enroll in these courses, but require either an instructor permission number (please email the instructor) or assistance from the data science help desk (see above).

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