The Passion for Data Science

Passion for a subject is developed after exposure. After kids grow up immersed in the excitement of basketball, many want to become professionals. The wonder of looking through a telescope, becoming captivated by a planetarium, or taking a mind-bending astronomy class can drive the passion for astronomy. Many doctors found their passion in toy medical kits, the satisfaction of helping others, or the thrill of seeing the complex interior of the human body for the first time.

For me personally, I will never forget my computer running through the night to convert hundreds of thousands of Amazon reviews to determine whether the reviews were helpful or not. I had a hard time sleeping. I couldn’t wait to see the results. When I awoke and saw machine learning scores of around of 80% accuracy, I was hooked.

Exposure to data science may come in a variety of forms. At Berkeley Coding Academy, we immerse students in the experience of becoming a data scientist. We teach students how to program, how to analyze big data, and how to build machine learning models to make meaningful predictions. In our 3-week intensive summer program, BCA students get the feeling of what it’s like to work as a data scientist, and many develop a real passion for the subject.

I teach data science because I have great passion for the subject. Delivering meaningful machine learning predictions after manipulating data and adjusting hyperparameters gives me a rush. Producing beautiful, informative graphs brings me real joy.

Data science is a subject where the rush and passion come after the hard work. Errors must be overcome. Code must be reorganized. Disappointing results may require multiple re-workings. Data science requires hard, focused work. But when that beautiful graph appears, or machine learning predictions exceed expectations, passion often follows.

It has been said that passion cannot be taught. This may be true, however, when students are given passionate teachers, and early exposure, passion is more likely to follow.

Corey Wade

Corey is the founder and director of Berkeley Coding Academy. He is the lead author of The Python Workshop, the author of Hands-on Gradient Boosting with XGBoost and scikit-learn, and a regular writer for Towards Data Science.