Tag Archives: masters

Georgia Tech Masters in Analytics for Less than $10k

Georgia Tech University just announced a new online master’s degree in Analytics.

Georgia Tech Creates First Online Master of Science in Analytics Degree for Less Than $10,000

The degree will begin in August 2017 and will be fully online. It will offer 3 tracks:

  1. Big Data
  2. Analytical Tools
  3. Business Analytics (coming at a later date)

Data Science Tech Institute Visiting Faculty

The Data ScienceTech Institute (DSTI) in France is starting 2 new master’s degree programs in data science. Both programs are highly innovative and offer a strong industry focus. Classes begin in October 2015, and each program is limited to 30 students. Therefore, if you are interested, it is important to apply as soon as possible.

The other day, the faculty at DSTI were announced. I am honored to say I was selected as one of the faculty. Thus, I will serve as a visiting faculty member for portions of the program.

DSTI offers 2 master’s degree programs:

  1. Data Scientist Designer – Located in Paris, this 2-year program is part-time and focused on working professionals looking to transition or enhance skills in the data science field. The course will rotate between 2 and 3 days a week.
  2. Executive Big Data Analyst – Located in Nice along the French Riviera, this program is a more traditional intensive 16-month program targeting full-time students.

If you are in France or Europe or interested in studying in France, the programs from DSTI are definitely worth a look.

3 Questions When Choosing a Data Science Program

I was honored to write a guest blog post for Master’s in Data Science. The site contains a very detailed list of graduate programs in data science. The post I authored is title:

3 Questions to Ask Before Choosing a Data Science Program

Not to ruin the post, but the 3 questions are:

  1. What is my Background?
  2. What are my goals?
  3. Does location matter?

Head on over to Master’s in Data Science to see all the details about why those are 3 important questions.

$10M for University of Virginia Data Science

The University of Virginia just announced a $10M endowment to support its new Data Science Institute.

The University of Virginia is in the closing stages of creating a Master of Science in Data Science (MSDS) and the eventual goal is to have an undergraduate minor and a Ph.D. program in Data Science. The curriculum for the MSDS contains a nice mix of math, computer science and statistics courses. It even includes coursework in visualization. Also, the program appears to be an entirely new program and not just the renaming of an existing program.

The University of Virginia is definitely taking the correct steps to become a recognized leader in data science education.

New Berkeley Online Data Science Degree

The University of California at Berkeley just announced a new masters degree in Information and Data Science (MIDS). The program is targeted to be completed entirely online with the exception of a one week visit to the campus. The program has a approximate cost of $60,000 for the 27 required credits. The curriculum looks good. It includes: machine learning, data analysis, visualization, big data processing, and privacy/ethics. The initial class of students will start in January of 2014.

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.