Brandon Rohrer (along with others) created an excellent resource for academic programs, Industry recommendations for academic data science programs. The resource is authored by a number of industry data scientists and university faculty. It is collection of useful information for college data science programs. Here are some of the topics:
Plus, the site is growing, and new information is frequently being added. If your college/university is launching a data science program, this resource is a must read.
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.