I’m three weeks into my 12-week Data Science Immersive - it’s a good time to look back on how these three weeks have passed and what I have gained from it.
Prior to the Immersive, I picked up Python through online courses and took the Part-Time Data Science course at General Assembly and I think that gave me a strong foundation for the Immersive. I had a break between the Part-Time and the Immersive and looked through a couple of machine learning and data analytics courses. That really helped in my ability to understand the concepts and skills we were going through in class.
One thing I really liked was how our lesson resources were formatted. Instead of traditional slides, our content was hosted on Jupyter Notebooks as a slideshow and that was really useful for me - I could simply add a new cell and jot down notes right underneath the slide (plus there was markdown support), and any code I wanted to test could go right there too!
On this topic, I usually like having the lesson materials beforehand so that I have time to look through it before class but we haven’t really had that. Materials will only be pushed to GitHub just right before the lesson starts - maybe I should include that as one of my suggestions/ requests.
It’s great having in-class labs - it’s a timely test of whether we’re able to grasp the concepts and apply them, and of course, the more I practice the more easily the code comes to me. The labs also push us to check the documentation so that we can learn more on our own and not just rely on in-class materials.
We just had our first group lab yesterday (Friday, October 7, 2016) on the Times Higher Education World University Rankings dataset. It was fun and I look forward to writing about it in more detail in a future post - keep a look out!
It’s been great meeting new people. Even met a fellow Singaporean! What are the odds?
Many of us came from diverse backgrounds and it was interesting hearing about why everyone was taking the Immersive. I’ve learned a lot from the questions being asked in class and I’ve heard so many great ideas too. It’s like they say, you don’t know what you don’t know until someone asks a question you don’t know the answer to.
One of the main reasons I’m doing the Immersive is because I’m looking for a career in data science. Outcomes is General Assembly’s career support curriculum, and it’s pushing me out of my comfort zone in preparing for a future job search. I’m grateful for it and I’m really excited to see what the various assignments will bring me.
It’s still a little early to tell how effective Outcomes will be for me, but I’ll be back with more in the later weeks.
Meetups seem to be a big part of the tech community and it’s no different for data scientists. In three weeks, I’ve been to my first three meetups and it’s amazing learning about the community, learning about how we’re moving forward in data science, and just hearing about the projects that people are participating in. I even reconnected with a course mate from my Part-Time course!
It’s been a great first three weeks and I’m really looking forward to learning more in the coming weeks. Writing this post has made me think about what’s important to me and what has been going well so far - it’s a helpful reflection and will keep me focused on my goals in the coming weeks.
Thank you for reading this long post on my thoughts and ramblings, I look forward to writing more posts on my projects and labs - I hope you’ll enjoy them!