#66DaysOfData — Round 2 Recap
A few days ago, I finished the 66th day of my second round of the #66DaysOfData challenge. To celebrate, I wanted to do a recap of an extremely exciting round, filled with projects, ideas, events and, most of all, great prospects for the future.
Let me start by understanding the differences between the first round and this one. Last year, when Ken Jee started this challenge, I took it as a way to build the specific habit of learning and/or practicing something related to Data Science every single day. From taking a course, solving a challenge, reading an article, watching a YouTube video, and the like. I had a blast, studied a lot, learned plenty, but the most amazing part of the challenge was, that it allowed me to connect with hundreds of amazing people who are working or interested in Data Science. This inspired me to do more for the community, and hence, it sparked the start of my Road to Data Science series of articles, which I am still writing (although the last few weeks it has been slow progress).
Because of this, my second round had to be related with giving back to the community. Initially, apart from the Road to Data Science series, I started a #66DaysOfData set of articles. My idea was to share part of what I do at ADA Intelligence, at least, what I can share. So, the first few days, I was constantly writing about building a Machine Learning model to predict attrition. It started with using the teachings of Biostatistics to build an algorithm without Machine Learning. Then, I was going to move on the ML version, and this is when things started to get interesting.
Early January, a couple of days after starting the second round, I was contacted by the Data Science GO organization, who invited me to talk about my Road to Data Science on their #DSGOConnect event. I have to say, it was a blast, a 30-minute talk followed by an amazing hour long Q&A in which I got to talk to many amazing people, data veterans and rookies alike. You can check out the whole thing on my YouTube channel (more details about this later).
After this event, I started talking to A LOT of people, from established Data Scientists to students to other professionals that, like myself, are transitioning into data science from other fields. The biggest issue I heard from most people, is how hard it is to get a job, even though there is an increasing need in the market for Data Scientists, the processes to hire them are still rough around the edges and hard to understand for both future employees and recruiters. The number one issue for all of them: experience. The truth is there are just not enough experienced data scientists out there. But how do you get experience without getting a job first. This led me to put two things that I am passionate about together, Data Science and entrepreneurship.
A brief side trip about this. I have been an entrepreneur and intrapreneur for the biggest part of the last 20 years, building independent professional businesses, and a couple of companies. Also, since 2013, I have been helping hundreds of entrepreneurs transform their ideas into actual businesses. Even last year, during the pandemic, my wife and I joined the Company Builder program to coach and mentor over 170 projects from Latin America, it was an amazing experience.
Back to the main adventure, what was born, through the encouragement of many people and the incredible support and work of my wife, was the DATApreneur initiative. A place where Data people of all kinds can get together, discuss problems, ideas, get together and have guidance and mentorship to move forward and create interesting products and services they can sell and create businesses. Feel free to join our discord channel here.
At this point, I am writing an article series, running a discord channel, and of course, working. But like always, when good things happen, they just keep coming.
Sometime in February, I was contacted by the Open Data Science Conference, and offered a talk for their AI + Career Lab and Expo, being right off the heels of opening the DATApreneurs initiative I, of course, jumped happily at the opportunity. The subject of the talk: Build your Own Job, and of course, I will be talking about DATApreneurship. This is happening tomorrow, so if you are reading this today, you can still sign up by clicking here. If you miss it, do not worry, I will update this article with the video once its in my YouTube channel.
Then, one of the best Data Scientists I know, Serg Masis, recommended me for a talk on the Python for ML and AI Global Summit, they contacted me, and of course, I said yes. Since it is a python-oriented event, my talk will be about the Zen of ML, inspired by the Zen of Python I am proposing we work together to define the principles that should guide our work, this will happen on the 9th of April. You can sign up here. Will be the Zen of ML as a github repository as soon as I finish it and linking to it here.
Finally, the great people at Geekle, who organize the Python Summit, asked me if I wanted to do a workshop during the summit. Obviously, since I am apparently not doing much, I said yes. And ho and behold, surprise, I will be doing a DATApreneurship Workshop. So if you are interested in learning how to start with a problem and end up with a business, sign up here for the workshop next week (April 9th).
And that is that. Oh wait, I said finally on the last paragraph but have not yet told you about my YouTube channel. Well, after many suggestions from people, and especially from my wife, who I have learned will push me in the right direction always, even when I am being stubborn about something (which is a lot), I opened my YouTube channel and will start creating video content very, very soon. For now, there is one video of my first talk this year, but you can subscribe, and it will soon be filled with what I hope will be useful and entertaining content. Check it out here (and subscribe).
And that is really it. It has been fun, and cannot wait to start a third round in a few weeks, probably focused around video content (but will keep the articles coming).
Jack Raifer Baruch
Follow me on Twitter: @JackRaifer
Follow me on LinkedIN: jackraifer
About the Road to Data Science — #66DaysOfData Series
Road to Data Science series began after I experienced the first round of Ken Jee´s #66DaysOfData challenge back in 2020. Since we are starting the second round of the challenge, I thought it would be a good idea to add small articles every day where I can comment my progress.
I will be sharing all the notebooks, articles and data I can on GitHub: https://github.com/jackraifer/66DaysOfData-Road-to-Data-Science
Please do understand I might have to withhold some information, including code, data, visualizations and/or models, because of confidentiality regards. But I will try to share as much as possible.
Want to follow the #66DaysOfDataChallenge?
Just follow Ken Jee on twitter @KenJee_DS and join the #66DaysOfData challenge.
You can also reach out to me at any time through LinkedIN or Twitter.
