A Data-Driven Retrospective of My Master’s Degree

Two years ago, I finally committed to earning a Master’s in Data Science. After six months of grinding a full time job and coursework, I took the leap to focus entirely on school. To keep myself focused without the traditional 9-to-5 structure (or boss), I leveraged an old habit from my time in consulting: I tracked my time. What started as a way to optimize my daily productivity turned into a comprehensive dataset of my academic journey. This post offers a retrospective on my degree, quantified.

The big picture

I categorized my time into four main buckets:

• MSDS: The core coursework, lectures, and homework.
• PROJECTS: Career building, portfolio work, and external consulting.
• AREAS: Life maintenance (because the dishes don’t wash themselves) and productivity systems.
• OTHER: Rest, recovery, and breaks.

While coursework was a focus, I was also able to take advantage of the time to build a few portfolio projects. I wrote about many on Medium. One that sticks out is a personal finance app I built with Plotly Dash, Firestore and Google Cloud Run.

Click on the inner rings to zoom in. Click “MSDS” to see exactly which classes consumed the most bandwidth.

A series of sprints

A Master’s degree is a series of sprints followed by recovery jogs. For me, the first week of classes and the weeks leading up to finals were the busiest. If I got ahead, I could squeeze in some work on a portfolio project. I took more time for myself in the summer and got down to business in the winter.

Hover over the bars to see monthly summaries. You can double-click the legend items to isolate specific categories.

Consistency is key

This nod to the GitHub commit graph highlights the importance of making at least a little progress every day.

So long, wellness

Wellness featured briefly as a priority before falling off 🤣.

Watch the shift from foundational concepts like Statistics and Algorithms toward Machine Learning and AI over time. The chart also highlights the growing focus on my portfolio projects as I progressed in the Master’s.

Mornings are for deep work

Maybe the most interesting insight for me was when I did the work. I added up what I worked on for each 15 minute window of the workday. You can see the “probability” of finding me working on any given category in the charts below.

I am clearly a creature of habit. The charts reveal I prioritized deep work early in the day before the noise of the world caught up.

Hover over the bars to see how likely I was to be working on a given category by time window.

Learning out loud

I published my notes, research and musings as I went through my Master’s here on my Knowledge Hub. It’s still very much a work in progress (and always will be).

Concepts in my notes are linked like Wikipedia and form a type of knowledge graph. This animation shows the growth of that graph over time. Colors indicate topics: Math (lime green), Statistics (red), Computer Science (orange), books and literature (bright teal).

What’s next

While I look for my next opportunity, I’ll be pursuing a graduate certificate in Artificial Intelligence, diving into modern techniques in Generative AI and AI Engineering.

I’m eager to work in the “modern intelligence stack”, building tools that make documents and data more discoverable and actionable. I’m hoping to work with a team on

• AI-powered knowledge systems
• enterprise search
• knowledge graphs

(If you know a team working on challenges like these, I’d be grateful for an introduction.)

Thanks for reading this far! To my friends and family, thank you for understanding when I said I needed to study. To my wife, thanks for encouraging me to take the leap and supporting me throughout.

If you’re thinking about pursuing an advanced degree, I recommend it. There are many ways to break into this field, from self-study to bootcamps to advanced degrees. While I had been working in the field for much of my career, earning the Master’s gave me confidence that I had mastered the fundamentals and provided the opportunity to deeply understand topics in a way online tutorials and training often skip. Combining my studies with portfolio projects to apply and extend my learning helped me translate theory into real world application. I’m very much looking forward to my next challenge!