Tag Archives: college

NBA Basketball Analytics Hackathon

The National Basketball Association is hosting an Analytics Hackathon.
Application are accepted until August 6, 2017 and the actual competition occurs on September 23-24, 2017. The competition has 2 focus areas:

  • Basketball Analytics
  • Business Analytics

The prizes for winning consist of:

  • Lunch with NBA Commissioner
  • A trip to the All-Star Game
  • Tickets to a game of your choosing

To be eligible, you must be:

  • At least 18 years old
  • An undergraduate or graduate student

Good Luck!

Valparaiso University is Turning Homework into Social Change

Recently, I had the honor of speaking with Dr. Karl Schmitt from Valparaiso University. He is the director of the Data Science undergraduate program at Valparaiso University. We had a very nice discussion, and I thought I would pass along my summary.

What are the Details of the Valparaiso Undergraduate Program?

The program is housed in the Mathematics department and it is designed to be fairly interdisciplinary. It consists of four parts.

  1. Math
  2. Statistics
  3. Computer Science
  4. A Separate Focus Area

The separate focus area can be from nearly any other department and is targeted at building some domain expertise. Although not required, a double major is encouraged.

One of the most unique and excited aspects of the program begins during the first year. Students take Introduction to Data Science, which has few prerequisites and serves as motivation for the remainder of the program. Valparaiso partners with non-profits and government agencies to provide the first year students with hands-on experience solving problems for social good. Examples include Meals on Wheels, mapping with the United States Geological Survey, and a child welfare non-profit. Then, the junior and senior students are involved with a capstone project that can be a continuation of the first year project, some other social good project, or students can serve in a consulting capacity to other departments on campus.

What skills Do You expect Valparaiso Data Science Graduates to Have?

There are a few basics skills that make sense for data science: coding, database skills, statistics, and general math. In addition, Valparaiso grads should also know how to talk, write, and create videos about mathematical concepts. Finally, ethics is an essential portion of the program. According to Dr. Karl Schmitt,

I want my students to graduate with ethics related to data science.

To enforce that statement: ethics case studies are required of all students, it is a key learning objective of the projects, and ethics is integrated into all the classes so students understand the importance. Students need to be able to do the hard data science, communicate the results and care about the consequences.

Why Choose Data Science as an Undergraduate?

It is a utility degree that is in strong demand in nearly every field. As companies continue to understand the usage of data, having data skills is going to get increasingly more crucial. Data Scientist are going to be (currently are) in demand for human resources, supply, sales, technology and many other awesome jobs.

Why Valparaiso for Data Science?

There are a number of reasons:

  • Good University Size – It is easy to double major and engage with things outside the major, plus disciplines are very connected which allows for collaboration.
  • Writing/Communication is Integrated Throughout – Many people can crunch numbers, but Valparaiso graduates can express discoveries. The students get that from the very beginning.
  • Projects – All students will have experience and examples of projects to demonstrate.
  • Finally, students have an opportunity to turn their homework into something that matters!


Thank you to Dr. Karl Schmitt for the interview and to Valparaiso University for Sponsoring Data Science 101.

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 College Programs Across the Globe [Interactive Map]

Continuing this weeks theme on data science colleges, the nice folks at Silk.co created an interactive map of the Data Science University Programs across the globe. Click the map to view the interactive visualization.

Where are the Programs?

Global Map of Data Science Colleges
Map indicating the location of all the data science college programs

Based upon the visualization, it is easy to see most of the programs are in the United States and Western Europe.

What About Degree Types

Data Science Breakdown by Degree Type
Data Science Breakdown by Degree Type

The data can also easily be broken down by degree type and how the degree is delivered (online/on-campus).

What is Silk.co?

To state it simply, Silk.co is a place to very easily store and visualize data. It looks pretty awesome.

Data Science Colleges by US State

US Data Science Colleges
US states with the most data science college/university degree programs

Creating the Awesome Data Science Colleges List has opened the data for some analysis. The above chart shows the states with the most data science programs based upon the total number of colleges in the state (dark red is best, followed by orange, followed by yellow, and finally black is for states with no data science programs).

The Top States

  1. Washington D.C.
  2. Colorado
  3. Massachusetts
  4. South Dakota
  5. Nebraska
  6. Indiana
  7. New Hampshire
  8. Maryland
  9. Illinois
  10. Pennsylvania
  11. New York
  12. Michigan
  13. Arkansas

The States Needing to Create Data Science Programs

  • Alaska
  • Delaware
  • Hawaii
  • Idaho
  • Kansas
  • Maine
  • Mississippi
  • North Dakota
  • New Mexico
  • Vermont
  • Wyoming

See the original post at Need to Learn Data Science? These States are the Best! and the analysis at Create US States Choropleth for Data Science Degrees.

Awesome Data Science Colleges List

I recently compiled a huge list of colleges and universities with data science-related degree programs. The compiled list is available on Github as Awesome Data Science Colleges.

I encourage you to contribute to the list if you know of missing programs.

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.

List of Over 200 Data Science College Programs

My previous list of Colleges with Data Science Degrees has grown very large, and numerous people have requested the ability to sort and/or filter. Thus, I built a new list. It is available at: Data Science Colleges. As far as I know, this is the most comprehensive list of data science programs available. Here are some of the features it offers:

  • Over 200 Programs
  • Certificate, Bachelors, Masters, and Doctorate programs included
  • Sort and Filter Programs
  • US and International
  • Program Name
  • Location
  • Online Programs
  • Ability to download the raw data as CSV or JSON

Yes, you read that last one correctly. All the data is freely available for you. If you do use the data for something, I would love to know and potentially blog about it.

The list will continue to evolve. If you find any broken links or missing programs, please leave a comment. Also, please leave a comment if you can think of ways to improve the list.

You Don't Need a PhD to do Data Science

Many of the top data scientists you will read about or hear speak have PhD degrees. Therefore, many people think a PhD is a requirement for becoming a data scientist. That is completely not true. There is a lot of work in the data science field that does not require a PhD. In all actuality, there is not a lot of data science work that does require a PhD.

What is a PhD and why would a person get one? A PhD degree is a research degree that usually takes between two and five years of study beyond a master’s degree. The majority of the program will be focused on researching and expanding upon a very specific topic. A PhD student will push the edge of known human knowledge.

In daily tasks, most data scientists do not go that far and do not need a PhD. Most of the necessary skills can be obtained at the bachelors or masters level. Combine that education with the amazing tools available and some experience and being a data scientist is definitely achievable.

The reasons many data scientists have PhD degrees are because of the curiosity and love for learning. Those are essential traits of both a data scientists and PhD students. However, you can be curious and love learning without attending enough school to obtain a PhD.

All of this is not to say that earning a PhD is bad. If you really love learning, thrive in the academic environment, and have the desire; then definitely go for the PhD. However, do not let a lack of a PhD stop you from doing data science.

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.