Data Science is such a broad field that includes several subdivisions like data preparation and exploration; data representation and transformation; data visualization and presentation; predictive analytics; machine learning, etc. For beginners, learning the fundamentals of data science can be a very daunting task especially if you don’t have proper guidance as to the necessary training required, or what courses to take, and in what order. Before discussing the degree training programs that could easily lead to data science, let’s discuss the essential skills needed for data science.

In a previous article (Data Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science), I discussed 10 essential skills that are necessary for practicing data scientists. These skills could be grouped into 2 categories, namely, technological skills (Math & Statistics, Coding Skills, Data Wrangling & Preprocessing Skills, Data Visualization Skills, Machine Learning Skills,and Real World Project Skills) and soft skills (Communication Skills, Lifelong Learning Skills, Team Player Skills and Ethical Skills).

While there are several skills needed in data science, due to its multidisciplinary nature, the 3 basic skills that could be considered as prerequisites for data science are mathematics skills, programming skills, and problem-solving skills.

A degree in an analytical discipline would provide you with the fundamental skills needed in data science. Everyone that has a strong background in an analytical discipline could basically learn data science via self-study.

If you have a background in an analytic discipline and you are considering data science, here are some resources that you can use for self-study:

(iii) Applied Data Science with Python Specialization (the University of Michigan, through Coursera)

(iV) “Python Machine Learning”, by Sebastian Raschka. This book provides a great introduction to data science and machine learning, with code included: “Python Machine Learning”, by Sebastian Raschka. The author explains fundamental concepts in machine learning in a way that is very easy to follow. Also, the code is included, so you can actually use the code provided to practice and build your own models. I have personally found this book to be very useful in my journey as a data scientist. I would recommend this book to any data science aspirant. All that you need is basic linear algebra and programming skills to be able to understand the book.

Let’s now discuss 5 best degree programs that can easily lead to data science. I will try to rank these programs, starting with best, and walking my way down. My ranking could be bias, I guess due to my background, but please bare with me.

I would like to place physics at the top of my list. I may be bias here, given that I myself I’m a physicist by training. But I think this ranking is well justified. A physics degree is one of the most versatile degree programs out there. A physics degree provides solid foundations in problem-solving, analytical skills, mathematics skills, and programming skills. These are skills that are easily transferable. This explains why you can find physics degree holders working in diverse areas such as academia, technology, banking and finance, research and development, software engineering, law, military, data analyst, etc.

If you are currently in a physics degree program and are considering data science, make sure you take some programming classes. Some background knowledge in programming is all what you need in data science. Also you may take a few classes in basic and advanced statistics and probability.

I would place mathematics as second in my list. Just like physics, mathematics is also a very versatile field and a background in mathematics can lead to several disciplines such as banking and finance, engineering, health sector, research and development, etc. A solid background in mathematics and statistics is the most important skill in data science.

If you are currently in a mathematics degree program and are considering data science, make sure you take some programming classes. Also, it’s important to take some classes too in basic and advanced statistics and probability.

A computer science degree is placed third in my list. Just like physics and mathematics, computer science training programs provide excellent foundation in problem-solving, mathematics, and programming skills. Programming skills are crucial in data science.

If you are currently in a computer science degree program and are considering data science, make sure you take some math classes such as calculus, linear algebra, statistics and probability, and optimization methods.

Any engineering degree program such as mechanical engineering, electrical engineering or industrial engineering will provide you the necessary analytical skills that are essential for data science.

If you are currently in a engineering degree program and are considering data science, make sure you take some programming classes and some basic and advanced courses in statistics and probability.

A degree in one these fields could also serve as a pathway to data science. The analytical skills provided in these programs may lack the mathematical rigor compared to programs like physics and mathematics, but a degree in economics or accounting will provide one with business skills, that are essential in the real world application of data science.

If you are currently in an Economics, Accounting, or Business degree program and are considering data science, make sure you take some math classes such as calculus, linear algebra, statistics and probability, as well as programming classes too.

In summary, we’ve discussed 5 degree programs that could serve as a pathway to data science. Anyone with the right motivation and passion can learn the foundations of data science. However a background in an analytical discipline such as physics, mathematics, computer science, engineering or economics would serve as an added advantage.