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Career Transition Towards Data Science: Planning a Learning Sabbatical

At the time of writing this post, I am nine months into my learning sabbatical. You can read about my journey here: “Career Transition Towards Data Analytics & Science”. Today I will share with you how you can plan your own, unique learning sabbatical, regardless of its scope and duration – anywhere between 1 and 12 months. Let’s get started.

Begin with the end in mind

If you have ever read Stephen Covey’s “7 Habits of Highly Effective People” you are familiar with the concept of picturing the end result before you even get started. I cloned that insight with another great piece of advice I found in another book: “Change Your Questions, Change Your Life” by Marilee Adams.

Apply question thinking

Question thinking is a very simple concept: ask more questions than you give answers. Talk less, listen more. Acquire an investigative mindset. Only accept answers that are beyond the boundaries of what is already known to you. That way, you will be forced to connect with and talk to people you have never spoke to before, and thus get new insights.

I found the combination of “beginning with the end in mind” and “question thinking” to be extremely powerful. Let’s see how that applies to planning and taking a learning sabbatical.

Melk Abbey Library | Source: Wikipedia (image released into the public domain by its creator)

#1 Question: What monetizable problem solving skills can you realistically acquire?

Setting the goal to become a data scientist is too generic. Besides that, a 12 month sabbatical won’t get you there anyways. But that’s a whole different story. Instead, ask yourself:

“What problems do I want to be able to solve, once I finish my learning sabbatical?”

In order to answer that question, you have to go out and talk to people. You need to understand what pain points your potential employer or customer has before you start your learning sabbatical. Reverse engineer from there:

“Is it feasible for me to acquire the skills needed to solve that problem?”

Again, talk to people, this time to those, who already have those skills under their belt. Third:

“How much money can I make?”

I borrowed this thought process from a third book: “Good to Great” by James C. Collins. The rationale is that there has to be:

  • demand for what you have to offer
  • you have to be good at it
  • and it needs to be potentially profitable

You can’t compromise on any of those three. For example, it does not really make sense to invest into building up skills for an overcrowded market - demand is there, but you can barely monetize your skills because of cut-throat competition.

#2 Question: Do you have the means for a learning sabbatical?

Depending on the duration of your learning sabbatical, the financial burden can be pretty high. You can go for a one, three, six or twelve month learning sabbatical.

“Can I sustain for 12 months without an income?”

If you plan for a 12 months learning sabbatical, but you run out of cash after 6 months, it’s going to be nearly impossible for you to keep going. If you only have enough cash for a 3 months sabbatical, just do exactly that: a 3 months sabbatical. Improvising does not work here. Think 5P: “Proper Preparation Prevents Poor Performance” (not sure where I found this piece of wisdom).

“Can I cut my expenses?”

Even if you have piled up enough money to do a learning sabbatical: cut expenses wherever you can. You never know, some unexpected expenses might occur. Besides that, you will sleep better knowing that you’re burning less cash than you initially anticipated.

“Do those around me understand and support me?”

My learning sabbatical generated six figure USD opportunity costs. Besides that, once I sold my car and moved into a smaller apartment, my friends and relatives started to worry. Some of them did neither comprehend nor support the idea of investing into my future career.

Be prepared that you will clash with some people. Can you make a compromise? Or, if a compromise cannot be found, are you willing to make tough decisions?

The social cost of taking this route can be pretty high. In my case, it cost me my marriage. If you are in your late 40s like me, and you feel urged to re-learn, it might be perceived as an intellectual declaration of bankruptcy. Going through this process can be very liberating though. Plus, the potential gratification is enormous, not only in financial terms, but also intellectually and socially.

#3 Question: How do you learn?

I’m an autodidact with a poor academic pedigree. You might hold a PhD. Each of us likely has a different learning pattern. I am geared towards learning things I can immediately put at work. That way, I work my way through from one practical skill to another, and thus I build up expertise. Finally, all those little bits and pieces come together and rearrange themselves into a bigger picture. How about you?

Regardless of what modus operandi works best for you: Pick the best teachers you can find. For me, the best teacher for all things Excel and beyond is Mike Grivin, who runs the ExcellsFun channel on YouTube with more than 100 million views to date. As far as Python and statistical machine learning goes, my absolute favorite teacher is Kevin Markham, who owns Dataschool.io. Mark also runs a fantastic YouTube channel.

Unlike in school, you can just replace each of your teachers

I take every opportunity to find the best teachers on earth. If the way someone teaches does not resonate with me, I move on to the next one.

#4 Question: Can you do it in 10x less time?

Take Python and Pandas as an example. You can take an online course which will require you to invest a full month of learning effort just to acquire the very basics. Likewise, you can get there in two days. I keep a laser sharp focus on that question.

"What are the minimum viable skill to get the job done?"

 A 12 month sabbatical sounds like a lot. But, boy, time flies. I can tell you that. You can waste a lot of time on learning things you will never need in your entire life. That being said, I always ask myself:

"Do I really need this?"

Because time is money. Every single day I spend learning has a price tag, and I want to make sure my learning efforts pay off.

#5 Question: How do you get to plan B?

“Getting to Plan B” is a great book written by Randy Komisar, partner at one of the world’s leading venture capital firms. The key message is that if you start a venue, you do so with a plan A in mind – which rarely, if ever works out. In that case, you have to get to plan B as quickly as possible.

It’s the same with a learning sabbatical. You begin with the end in mind, but as times passes by, you realize: “Wait a minute, does that goal even make sense?” And then you readjust. Initially, I was geared towards no-code platforms, but I then realized their severe limitations. I took a more balanced approach of blending business application and programming skills while I already was on my learning path.

#6 Question: How do you make sure you stay relevant?

You should cast yourself away at times, turn off your phone and just learn without any distractions. But if your entire learning sabbatical looks like that, you run at risk doing stuff that is irrelevant to the outside world (aka your future employer or customers).

Make sure you have one tiny little work assignment on the side. That way, you make sure that you don’t lose contact with the corporate world, and thus with reality.

My last piece of advice for today: Watch Sam Altman’s series on How to Start a Startup. If you think of your knowledge as of a product, you will learn a lot from this amazing Stanford series. What specifically? That’s my assignment for you: Watch this series and find the answer by yourself. Enjoy!

This is my story. I am curious to hear about yours. Maybe you have questions I didn’t answer in my write-up? Please leave a comment or reach out to me via email [email protected] or via LinkedIn. Thank you!

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Comment by Ekaterina Ponkratova on Wednesday

Hi Rafael,

Thank you for the article! I am in my, hm, I think 6-months sabbatical. I had thought that my studying should have some tangible result, so I started #100DaysOfCode challenge at the https://www.100daysofcode.com/. The plan is to learn a new algorithm every day, for example, and then, try to implement the concept, using Python / R. Let's see how it goes, I am just on day 6.

Good luck with the self-discovery and ds-discovery!

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