Awhile ago, I recorded a Facebook Live on Tips for Data Science Students. It goes along with the following post: Getting the most from your Data Science Masters Program.
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
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.
- Computer Science
- 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 University just announced a new online master’s degree in Analytics.
The degree will begin in August 2017 and will be fully online. It will offer 3 tracks:
- Big Data
- Analytical Tools
- Business Analytics (coming at a later date)
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?
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
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.
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
- Washington D.C.
- South Dakota
- New Hampshire
- New York
The States Needing to Create Data Science Programs
- North Dakota
- New Mexico
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.
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.
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:
Not to ruin the post, but the 3 questions are:
- What is my Background?
- What are my goals?
- Does location matter?
Head on over to Master’s in Data Science to see all the details about why those are 3 important questions.
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
- 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.
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.