Site icon Ryan Swanstrom

Choosing a Data Science Graduate Program

Due to the large list of Colleges with Data Science Degrees, I receive a number of email inquires with questions about choosing a program. I have not attended any of the programs, and I am not sure how qualified I am to provide guidance. Anyhow, I will do my best to share what information I do have.

Originally, the list started out with 5 schools. Now the list is well over 100 schools, so I have not been able to keep up with all the intricate details of every program. There are not very many undergraduate options, and the list only contains a few PhD programs, so the information here will be focused on pursuing a masters degree.

Start by asking 2 questions:

  1. What are my current data science skills?
  2. What are my future data science goals?

Those 2 questions can provide a lot of guidance. Understand that data science consists of a number of different topic areas:

  1. Mathematical Foundation (Calculus/Matrix Operations)
  2. Computing (DB, programming, machine learning, NoSQL)
  3. Communication (visualization, presentation, writing)
  4. Statistics (regression, trees, classification, diagnostics)
  5. Business (domain specific knowledge)

After seeing the above lists, this is where things get cloudy. Everyone brings a different set of existing skills, and everyone has different future goals. Here are a few scenarios that might clear things up.

Data Scientist

The most common approach is to attempt to build knowledge in all 5 topic areas. If this is your goal, find the topic areas where you are weakest and target a graduate program to help you bolster those weak skills. In the end, you will come out with a broad range of very desired skills.

Specialist

A different approach is to select one topic area and get really, really good. For example, maybe you want to be an expert on machine learning. If that is your goal, then maybe a traditional computer science graduate program is what is best. In the end, you will be well-suited to be an effective member of a data science team or pursue a PhD.

Data Manager

A third and also common approach is from people that want to help fill the expected void of 1.5 million data-savvy managers. These people do not necessarily want to know the deep details of the algorithms, but they would like an understanding of what the algorithms can do and when to use which algorithm. In this case, a graduate program from a business school (MBA) might be a good choice. Just make sure the program also involves coverage from the non-business topics of data science.

Example

I think NYU is the best example of a school that can help a person achieve just about any data science goal. The NYU program is a university-wide initiative, so the program is integrated with many departments (math, CS, Stats, Business, and others). Therefore, a student could possibly tailor a program to reach a variety of future goals. Plus, New York has a lot of companies solving interesting data science problems.

Conclusion

There you have it. It does not narrow the choices down, but it should help to provide some guidance. Other factors to consider are length of a program and/or location.

Good Luck with your decision, and feel free to leave a comment if you have and good/bad experiences with any of the particular graduate programs.

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