My cohort and I celebrated surviving our first week of the Galvanize Data Science bootcamp! I know I was excited and nervous at the beginning of the week, not knowing how quickly we would move through topics, what the days would feel like, or who would be sitting in the classroom alongside me. It feels great to have answered many of those questions– especially meeting and getting to know my fellow bootcampers!
The focus this week was software engineering, including object-oriented programming and using a few key Python libraries. Big picture, I think my most important lesson learned is the importance of planning before starting to code. Thinking through the structure of how you want to address the problem and what you want to build really can make writing the actual code a lot smoother.
Lesson 1: There’s very little camping in bootcamp
One piece of advice that I am hoping to take to heart for the next 12 weeks reflecting each day on “what do I know now that I didn’t know yesterday?” I’m not sure if I’ll keep documenting that here, but at least for week 1, I identified the following (sometimes small) victories:
Day 1: I used sys.arg with ease to create a program I could pass arguments to when calling from the terminal.
Day 2: I felt my understanding of classes/OOP really grew today. I found the assignment to implement an interactive blackjack game really challenging but rewarding. At the end of the night, I had at least a basic, functional game up and running.
Day 3: I much better understand the different types of joins. This had definitely tripped me up before when using SQL.
Day 4: I now actually understand how you filter specific columns or rows from a Pandas dataframe. (Pandas is a popular Python library for data analysis). I’ve played around with Pandas before, but always used a lot of trial and error to select the column or row I care about.
Next week we move onto probability and statistics. I’ve taken a few statistics classes in the past, so I’m very interested to see how much is review and how much is new!