Numerous options are available for people trying to learn about data science. Better options tend to cost money. While self-paced learning can help introduce you to a topic and give you a foothold in the field, some of the best programs are intensive courses and “boot camps.” For this reason, I chose a local data analysis boot camp with a solid reputation and a relatively low price for the number of class hours.
Collaborative projects helped prepared us to work in groups, and we used Github for version control. While the results of the projects were not always what I wanted, the experience was priceless.
Going into the class, I had done almost no coding for about 15 years. Only three months before, I had begun learning python programming for data science. So, the breadth of what I learned during the course was tremendous.
For me, the course had its ups and downs. We rapidly proceeded from one topic to the next. As soon as I grasped the material, we jumped to the next topic. The nine-hour-per-week course tested even the most knowledgeable among us.
Although, we met in a lecture hall for much of the class, we went remote during the COVID-19 outbreak. Remote work caused some unexpected challenges in both learning and collaborating on projects. Zoom conversations were not as clear as they might have been in person.
Throughout the experience, the knowledgeable instructor Edward Krueger, and the talented TAs Umair Khakoo, David Richter, and Douglas Franklin were always there to provide support and answer questions.
Like anything worthwhile, it was not easy. The remote work made things especially difficult for me because I get a lot out of face-to-face interaction. However, the skills that I learned in working collaboratively and remotely outweigh those difficulties.
I learned more in that course than in any other class that I have taken throughout my academic and professional career. I am now ready to use data to find insights, draw conclusions, model, and make predictions.