Why I Decided to Take Part in a Data Science and AI Boot Camp
August of last year, a lot of things came together. Not only did I suddenly end up in the hospital for a week due to a surprising medical condition. At the same time, I was let go from my last job, as the business unit I was working in as a product manager was shut-down. While the first situation by itself was pretty unpleasant, in combination with the second, it led to a great opportunity.
Given an extended termination period, I had time to step back and plot my path for the next part of my career.
What does the current environment of work look like?
No matter in which industry you are working, all share an increase in data availability and usage. Most business decisions nowadays are either supported or fully guided by data. And while a few years ago, Excel was still a skill that you could list on your CV, it is now expected as a given. If you want to show that you are used to working with data, more sophisticated solutions like Tableau, Qlik, or raw SQL are what recruiters look for.
But the availability of data is not just a driver for basic analytics and changing business decision making. It also leads to an increasing number of visible and invisible AI solutions in products.
Your commute in the morning is making use of automatically optimized route finding. Your email inbox has smart spam protection integrated, which is a prime example of a naive Bayes algorithm. Your online shopping break or your streaming choice in the evening is influenced by a recommendation system powering personalization. And soon we will start to interact with true conversational AI agents.
According to most predictions regarding the future of our work, we can be sure that the amount of data we are using is only increasing in the upcoming decade. This is especially the case looking at product development in tech, the field I gathered most of my experience in. Thus, who is not preparing for this might be in danger of being sidelined.
But what about my personal perspective?
As mentioned above, I worked as a product manager for the past years. Like most product managers, I did not plan to become one when I was a kid in school. It was a role I grew into due to a mix of coincidence and a general interest in management. What ultimately lead me into the profession was my interest in technology and how to build tech products. Hence, if I would have to place myself in the tri-force of product management between business, tech, and design, I would choose the following spot, with a strong tendency towards the first two.
Due to my tech interest, I already spent time outside of my work learning programming languages like JavaScript and Python, and got some experience in in HTML and CSS. Another part of my work as PM was using SQL and Tableau or Amplitude to generate info about user behavior on the fly when necessary. And while it was great to dig into all these skills besides my work and to use them from time to time, I missed immersing myself in it.
I also realized that it was once again time for me to change industries.
Having worked in or close to the gaming industry for the past years, I was yearning for new topics and challenges in other markets. I learned a lot during that time. I managed product teams of differing sizes on web and mobile products and got some experience in different agile management methodologies like Kanban and Scrum. So maybe I should actually follow that itch of getting deeper into the technology that will drive the upcoming years of technology?
How could I make use of my time in the best way and also get deeper into the ideas that will influence the upcoming years of tech?
Looking back, I do not exactly know when I had the idea of attending a boot camp for the first time. But soon after it happened, I started to do some floor tests (as we PM’s like to do). I asked several people who are more experienced in product management and data science than me, regarding their opinion.
Surprisingly, no one told me I should not do it or saw it as a waste of time. I still remember how it surprised me in the beginning. Picture the following situation:
Me: “…well…and I had this weird idea of doing an AI boot camp instead of going straight for the next job. But it would be three months I am loosing there.”
Conversation partner: “I like that idea. This is definitely the best situation to do something like that!”
Me: ”Aehm…what?”
Once again, I was also surprised how many quite important and definitely busy people in the industry are open to answer your questions if you just reach out to them via LinkedIn or mail. And there the general feedback I got was also somewhere between “Sounds like a refreshingly out of the ordinary idea” to “Why are you even still thinking about it. Do it!”.
But there was still one question that kept popping up in my head.
How can I make sure that I get what my money is worth?
There are plenty of technical boot camps around, especially in cities like Berlin. And as the demand for specialized boot camps is growing, more and more providers are offering them already. As a boot camp is a considerable investment of time and money, it is crucial to make sure to get the most out of it in terms of content and quality. The easiest way to check it is to do the following four things:
- Get some info about the content and teachers and ask some specialists you know what they think about the curriculum and staff.
If content or teachers are not up to par, you are better off getting a book out of a library or an online course. Nowadays, content is easily accessible; the communication of it and network makes the difference. - Ask to visit the facilities during a typical teaching day to see how it looks and feels.
You are going to spend a lot of time there, so better make sure you can stand it. You will also get a glimpse into the style of teaching and the group sizes. - If possible, attend a demo day.
Not all boot camps have one, but if they do, this is an excellent way of getting an idea regarding the quality of work and if the boot camp is well connected. So also, make sure that you are keeping an eye on the attendance list of the demo day. - Reach out to participants of earlier batches and ask for their opinion.
These people have made the investment already, and if they are not happy with it, why would you make the same mistake?
If you find yourself not being able to get all or most of the above-mentioned info, stay away from it. This is definitely a red flag.
Fast forward: End of January 2020
After spending my unexpected spare time making sure that I knew what my goal was and checking my options, I just recently finished the first of three weeks of Data Science and AI lectures at the Data Science Retreat in Berlin.
Will it pay off?
Most definitely, as I know what I want to get out of it: A more in-depth insight into what, in my opinion, will define significant parts of my future work life.
Would I do it again?
Given my current situation where it fits nicely into the time between jobs, I think the timing is perfect. And three months are not making a huge difference when you are setting it into relation to the rest of my projected career.
Would I recommend it to everyone else?
If you are up for some intensive three months during which you will forget if it is a weekday or the weekend, I think it is a great experience. But if you just want to spend some spare time with an exciting topic, I would recommend you to stay away from it. Good boot camps are called that for a reason. Especially if you want to get the most out of it.
So what am I going to do after the boot camp?
Nothing is cast in stone yet. I think I know where my strengths are and how I can combine my new insights with my previous experience. Obviously, a three months long course will not make a full-fledged and finished data scientist out of me. This takes experience and time. What I will get out of it is a deeper understanding of the underlying technology and theory. And also an excellent learning experience, which I already know I will miss again in a few months. So let’s see where this journey guides me. The most important part is a rough direction and momentum.
