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This page contains information for students in the Master of Science in Data Analytics program at George Washington University. Last Updated: 7/12/22 (New content at top)

Important: for student who started BEFORE Fall 2022: This page reflects the new DA MS course requirements for students starting in Fall 2022 or later. If you are on the old program, then you should check this Pre-2022 DA MS FAQ.

Frequently Asked Questions

What is the recommended sequence for full-time students?

  • Semester 1:
    • CSCI 6444 Introduction to Big Data and Analytics
    • EMSE 6765 Data Analysis for Engineers and Scientists
    • EMSE 6574 Programming for Analytics
  • Semester 2:
    • EMSE 6586 Data Management Systems for Data Analytics
    • First Required Track Course
      • CS Track: CSCI 6212 Design and Analysis of Algorithms
      • EMSE Track: EMSE 6575 Applied Machine Learning for Analytics
    • Elective
  • Semester 3:
    • Second Required Track Course
      • CS Track: CSCI 6364 Machine Learning
      • EMSE Track: EMSE 6577 Data-Driven Policy
    • Elective
    • Elective
  • Semester 4:
    • SEAS 6402 Data Analytics Capstone

This leaves your final semester light on course work, which many students find helpful as they apply for jobs and can focus their time on interview prepartion.

NOTE: The above schedule is optimized for students starting in a fall semester. If you begin in spring, EMSE 6574 is usually not offered. If you are in the CS track, we recommend taking CSCI 6212 instead, or if you are in the EMSE track you can pick an EMSE course without prerequisites to take as an elective.

What is the recommended sequence for part-time students taking 6 credits a semester?

  • Semester 1:
    • CSCI 6444 Introduction to Big Data and Analytics
    • EMSE 6574 Programming for Analytics
  • Semester 2:
    • EMSE 6765 Data Analysis for Engineers and Scientists
    • EMSE 6586 Data Management Systems for Data Analytics
  • Semester 3:
    • First Required Track Course (CSCI 6212 or EMSE 6575)
    • Elective
  • Semester 4:
    • Second Required Track Course (CSCI 6364 or EMSE 6577)
    • Elective
  • Semester 5:
    • Elective
    • SEAS 6402 Data Analytics Capstone

Can you help me understand the overall degree requirements?

  • The full requirements in the Bulletin are:
    • Complete the five Required Courses
    • Complete two Required Track courses for your focus area (CSCI 6212 and CSCI 6364 or EMSE 6575 and EMSE 6577)
    • Complete one more Elective course in your track’s department at the 6000+ level
    • Complete two additional electives. These can be 6000+ courses from any department, but if they are outside of CS or EMSE, then you need to get approval from your advisor first.

Do I need to take CSCI 6362 Probability for Computer Science as a Prerequisite for CSCI 6364 Machine Learning?

  • No. This is not required as long as you have a statistics/probability course at the undergraduate level. Taking EMSE 6765 Data Analysis for Engineers and Scientists will also meet this need.

How many courses do I need in my focus area (CS or EMSE)?

  • You must take at least 3 courses in the track you have selected – two are required and the third is any of your choice from that department.

Can I take course X which is not listed in the degree requirements?

  • Yes, it can be one of your 2 unrestricted electives. Contact your advisor for approval first.

I want to take a course from the CS department, but when I register it shows “Field of Study Restriction - Major”, can I still join?

  • Yes, but you will need to fill out the CS Department’s Registration help form. Contact your advisor or cs@gwu.edu for more information.

Can the SEAS 6402 DA Capstone course only be taken in Spring semesters?

  • The course is only offered in the spring. You should not take 6402 until you have completed the other four required courses. If you start the program in Spring, then we recommend taking it in your 3rd semester (i.e., your second spring, a semester before graduation). If you are not able to take the course at the normal time, you should consult with your advisor before your last semester about completing the capstone as an independent project.