This page contains information for students in the Master of Science in Data Analytics program at George Washington University. Last Updated: 9/15/19 (New content at top)

Frequently Asked Questions

The Bulletin lists two Capstone courses. When do I take these?

  • You should take SEAS 6401 Data Analytics Foundations and Practicum (formerly EMSE 6992 DataAnaly Foundation & Praticum) in Fall of your first year and SEAS 6402 Data Analytics Capstone in Spring of your second year.

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

  • You must take at least 3 courses in the track you have selected.

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.

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 go to the CS office (SEH 4000) and ask to fill out an RTF form to join the course.

What courses can I take related to Machine Learning?

  • EMSE 6575: Applied Machine Learning for Analytics (previously called “Data Mining and Processing” – see below), which is a more applied, less theoretical course, designed for DA students.
  • CSCI 6364: Machine Learning, which covers the theoretical basis for machine learning algorithms. However, to take this first you must take the prerequisite course CSCI 6212: Design and Analysis of Algorithms. A statistics course (CSCI 6362) is no longer a prerequisite. If you have taken 6212, then you can go to the CS office (SEH 4000) and ask to fill out an RTF form to join the course.
  • You can take both of these courses.

What courses can I take related to Database Systems?

  • EMSE 6586 Data Management Systems for Data Analytics. This is the preferred option and will satisfy the database course requirement for your degree.
  • CSCI 6441 Database Management Systems. This should not be taken unless the above course is unavailable.

(Spring 2019) What is the difference between EMSE 6575 Data Mining and Processing and EMSE 6992: Applied Machine Learning for analytics

  • We will be combining EMSE 6575: Data Mining and Processing and EMSE 6992: Applied Machine Learning for Analytics. Due to an oversight error on the part of the department/school, both courses were scheduled even though they are equivalent. The course will be held in Tompkins 410 on Wednesday from 6:10-8:40. If you intend to take this course, you may register for either and they will be combined.

(Spring 2019) I want to take CSCI 6444 Introduction to Big Data and Analytics. Which section should I sign up for?

  • For Spring 2019 you should sign up for the special section reserved for DA students (Section 10)

(Spring 2019) Some of the requirements listed on this webpage are different than in the Bulletin - which is correct?

  • You should follow the requirements listed in the GW Bulletin.
  • Here are a few updates that have not been applied to the Bulletin yet:
    - EMSE 6035: Marketing of Technology can be taken as an EMSE track elective course
    - EMSE 6992: Data Analytics Foundations and Practicum is a required course (counts as the first Capstone course)