
In my earlier post, I shared my approach to building self-directed learning projects. I emphasized, before jumping into any project, you should pick carefully and strategically what skills to invest in. In particular, prioritizing skills that are foundational, transferrable, and adjacent to your core competency are some of my criteria for acquiring new professional skills.
I also highlighted the importance of planning — from defining the objectives and key results, decomposing a project into concrete milestones, to surveying and sampling learning materials, these planning exercises can significantly reduce logistical complexity and enable you to deeply focus on learning itself.
In this second post, I will pick up where we left off and describe how you can develop habits and rituals to reliably execute against your plan. Furthermore, We will cover techniques that will further solidify your learnings such as doing drills for procedural learning, building mental models for conceptual learning, and using free recall and spaced repetition to remember facts. By the end of this post, I hope you will be inspired to develop your learning system as many others have. …

Recently, I came across a blog post written by Simon Hørup Eskildsen on how he approaches reading. It was an inspiring read because I did not know anyone this deliberate about the pursuit of reading. This kind of meticulous, thoughtful, system-level design thinking reminds me of Ray Dalio’s Principle:
Think of yourself as a machine operating within a machine and know that you have the ability to alter your machines to produce better outcomes
While I do not see myself as a machine, I did examine various aspects of my life and found that I tend to apply this type of thinking more rigorously when it comes to learning. In graduate school, I experimented with various studying strategies to make my day more effective. …

I recently came across a great book called “The Manager’s Path”, written by Camille Fournier. In this book, Camille describes the possible career paths of a technical individual contributor (IC) as one continues to grow in her career. I find this book illuminating because it touches on a rather common topic in the tech industry — “Should I transition from IC track to management track? If so, when is the right time?”. If you have been working as an IC for the past few years, chances are, you have pondered on this question already.
Given that this topic is discussed so extensively in engineering (see here, here, and here) and design (see here, here, and here), you would think it is all figured out by now. However, for a field as new as data science, I haven’t seen a whole lot of discussions about this topic just yet. After working in the field for more than half a decade, I have developed my own perspectives on how to think about this topic, so here we go! …

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