Man on a Mission Series
Some time ago, I stumbled upon the website Less Certainty, More Inquiry. If you click on the link, you’ll see that Darryl Blackport shares what he listens to or reads every week of the year. I found the concept intriguing and thought it would be a great fit for me, as I’m often immersed in studying or reading something.
This year, I’m taking inspiration from his approach. I’ll share what I study each month, providing a brief overview of the topics I’ve explored, focusing on what I found particularly interesting or useful. To kick things off, here are my learning goals for 2025. Let’s dive in.
What to Learn in 2025: Deep Learning
For most of my data science journey, I’ve taken a theory-first approach, focusing heavily on statistics. However, with recent advancements in tools like LLMs, I think it’s time for a shift. In 2025, I plan to delve into deep learning (a domain I’ve avoided so far) with a hands-on approach.
Here’s my roadmap for deep learning:
What to Learn in 2025: Sports Analytics
I’ve been passionate about sports analytics for nearly a year now and have made significant strides in basketball analytics. (You can check out some of my work here.)
This year, I aim to expand my focus by creating videos on football (soccer) analytics, in addition to basketball, on my YouTube channel. To prepare for this, I’ve started the following specialization:
Also, Dean Oliver’s new book, Basketball Beyond Paper, is on my reading list—it’s a must-read for anyone in this space.
What to Learn in 2025: Statistics
I consider statistics to be one of my stronger skills compared to other data scientists in the industry (at least in Turkey), but there’s always room for growth.
Currently, I’m halfway through Think Bayes, and I’m looking forward to Tom Faulkenberry’s upcoming book when it’s released.
There are specific topics, like meta-analysis, that I want to strengthen, but I don’t plan to tackle them systematically. Instead, I’ll explore them as curiosity strikes.
What to Learn in 2025: Production-Level Data Science (Maybe)
This one’s a “maybe.” Deep learning and LLMs are higher priorities, and the list is already packed. However, gaining production-level data science expertise could be beneficial in the long run.
For now, it’s something I’ll keep on the back burner, but we’ll see how the year unfolds.
A Final Note
This blog post was polished with help of ChatGPT! I write the whole piece and feed it to ChatGPT to improve the flow.
And that’s pretty much it for my 2025 learning goals. Stay tuned for updates!