3 Possible Ways to Get into Data Science
This article will discuss 3 possible ways of getting into the field of data science.
If you are interested in learning about data science, it is important for you to do some research about possible pathways that can lead you to the field of data science. This article will discuss 3 possible ways of getting into the field of data science.
1. Traditional College Degree
Several top universities offer traditional graduate-level programs in data science. Because these are graduate-level programs, most will require an undergraduate degree in an analytical field such as physics, mathematics, accounting, business, computer science, or engineering. These programs typically have a duration of 3 to 4 semesters for those who pursue full-time enrollment. Traditional programs come in different flavors such: Data Science Master’s, Data Analytics Master’s, or Business Analytics Masters. The cost of tuition for traditional face-to-face programs could be anywhere in the range of $15,000 to $40,000, not including living expenses. Thus, before pursuing a traditional college degree, do well to ask yourself the following questions:
- Should I consider an online program or a face-to-face program?
- Will the face-to-face program require me to relocate?
- How good is the curriculum?
- What are the prerequisites? Some programs require you to have completed some basic math and programming courses. Some would require GRE or GMAT test scores.
- What is the duration of the program?
- What is the cost of the program?
Online masters are extensions of traditional college programs. The advantage of online programs is that it is less costly and does not require relocation. Most online master’s program in data science or business analytics can be completed on average between 18 to 24 months. The cost for online data science master’s programs can be anywhere from $13,000 to $40,000.
MOOCs Professional Certificate/MicroMasters
There are so many excellent massive open online courses (MOOCs) in data science on platforms such as edX, Coursera, DataCamp, Udacity, and Udemy. The courses offered could be standalone courses, or in the form of specializations (professional certificate) or MicroMasters. These are offered by top universities such as Harvard, MIT, University of Michigan, Boston College, The University of Adelaide, University of California San Diego, University of California, Berkeley, etc. These programs are cheaper and affordable, and you can take courses at your own pace. The professional certificate and MicroMasters program costs are typically in the range from $600 to $1,500.
By dedicating some time, you can teach yourself the fundamentals of data science from these courses. Here are some of my favorite online data science specialization/MicroMasters programs:
- Professional Certificate in Data Science (HarvardX, through edX)
- Analytics: Essential Tools and Methods (Georgia TechX, through edX)
- Applied Data Science with Python Specialization (the University of Michigan, through Coursera
You can find out about more MicroMasters programs offered on the edX platform from this link: edX MicroMasters programs in data science.
In summary, we’ve discussed three possible pathways to data science. If you want, put in four years at a college (or more at a graduate school). This will give you a deeper understanding of the field, but if your circumstances don’t allow you to pursue a college degree, you can (with some passion and dedication) teach yourself data science through self-study. MOOCs provide great courses on a variety of data science topics, at a fraction of the price you pay for a traditional program. By dedicated the right amount of time and energy, you can learn the fundamentals of data science via MOOC specializations and MicroMasters.
Benjamin O. Tayo is a Physicist, Data Science Educator, and Writer, as well as the Owner of DataScienceHub. Previously, Benjamin was teaching Engineering and Physics at U. of Central Oklahoma, Grand Canyon U., and Pittsburgh State U.