You're Not Behind. You're Not Alone.
During my career as a music theory professor, I saw the same freshmen in my classroom five days a week. Our classroom, inevitably, became the site not just of learning a difficult subject at a fast pace, but also of discussions about what strategies could help you do that. As a Data Science Fellow, I’ve continued to rely on these strategies and wanted to share some of them with you as you consider NYCDSA. Writing these thoughts out, I found all of them revolving around two major ideas: 1. You’re not behind. 2. You’re not alone.
You’re Not Behind
When you first see the extent of the curriculum, you may feel overwhelmed. It has to be that wide to address all the foundational knowledge for today’s data scientist. With so much to learn, it’s easy to feel like you are always behind.
I've discovered in my chats with former and current boot campers that everyone feels behind at some point. The truth is that while everyone in a cohort sometimes feels behind, they are also ahead of and alongside each other in various ways. These differences come from our diverse backgrounds, bringing prior strengths and skills that contribute to our understanding of data science differently. The virtual nature of the cohorts allows a great diversity of backgrounds in our community, and we can all learn from each other.
After you start, you’ll find that your background will help you grasp some of the lessons relatively easily. Whether it’s the stats, the coding, domain knowledge, or communication skills, your experiences will help you pick up on certain parts of the curriculum more quickly than others. The others in your cohort will feel themselves as behind you at some point in the program, just like when you feel behind them. That we don’t have the same talents doesn’t mean the ones we have are any less valuable. As a musician, I always felt like I couldn’t play as fast and as high on my clarinet as my peers, but I could learn songs by ear and improvise better than a lot of them. In the same way, you’ll find aspects of the curriculum where you shine as long as you keep at it!
Make the most of the experience and strike the right balance between feeling behind and feeling like you already know the material. When a session feels too advanced, think of it as a sort of heads-up about vocabulary and concepts that will come up in your career. When more basic classes feel too easy, think of it as a chance to solidify what you’ve been learning.
I told Vivian a few months ago that I felt worried about falling behind in the program, and she comforted me by encouraging me to reframe my “timeline” from the weeks of the bootcamp to time I needed for "learning data science well and using it in my new career". On that path, none of us are behind.
You’re Not Alone
Our online instruction format allows incredible flexibility and global collaboration. It's easy to feel isolated, though, and that feeling can depress you and slow your learning. That’s why I urge you to capitalize on the synchronous portions of the program like the office hours and meetings with mentors. Be proactive about coming to live sessions. Turn your camera on, say “Hi”, ask questions, and message people who attended. Reaching out helps you feel connected and human as you learn, and the people at these sessions may become collaborators, coworkers, or friends in the coming years. Nearly everyone I’ve reached out to for advice on domain knowledge or help with a project has been willing to meet and chat.
Helping out doesn’t necessarily mean teaching: it can just mean lending support. For example, I joined a study group that doesn’t even talk about the material; we just come together virtually on Zoom with our cameras on to keep us motivated and focused. You’re less likely to allow yourself to procrastinate if you'll get caught! Even in a group like that, I know that I’m not alone and that I have people I can root for as they cheer me on, too.
If you keep at the front of your mind that you're neither behind nor alone, you’ll be set up for staying on track and learning well throughout the course of the program. Remember your long-term goal to launch a data science career, and stick with it. Happy studying!
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