How I Challenge Myself to Learn Data Science (as self-taught)
Last year in October 2021, I officially graduated from Bandung Institute of Technology! Happy? Over the moon guys! But also I am anxious to see what the future holds for me. Like most people, when you graduate from college the first thing you do is find a job that you desire.
I started to prepare my CV, and sent it to several companies and recruiters on LinkedIn. It is overwhelming finding a job, especially during pandemic Covid 19. Then, I was wondering “What is high demand job and most demand skills this year?” After I read some articles, most of them from LinkedIn. I’m so excited in Data Science because it’s The Sexiest Job of the 21st Century.
There are three top skills when people want to pursue career in data science such as Math/Statistics, Computer Science, and Domain Knowledge. My major is post-harvest technology, even my thesis is related to agriculture and I’m not an IT person guys! I don’t shift my career to data science because I love my major. I am just being realistic, what skill needs right now and what can I learn to get jobs. Besides, I can combine my knowledge in data science to agriculture. Now, I just have to collect dots and connecting them in the future like Steve Jobs said:
“You can’t connect the dots looking forward; you can only connect them looking backwards. So you have to trust that the dots will somehow connect in your future.”
So what should I do? Of course! I challenged myself to learn that skills for 6 months (as self-taught) and I did it! I land my first jobs in data science as a Business Intelligence in one of top Tech/Start up in Indonesia. So the questions is, how can I do it? In my case, I used the third approach. Here’s what I did:
1. Start with why, how, and timeline
There are many jobs needed in the pandemic era, such as digital marketing, video editing, content creator, etc. If I’m too stubborn to get a day job, why I choose data science? I have to find “Why”. If most people want a career in data science because salary, I don’t think it’s enough to keep me consistent in learning because I know learning new things is difficult so I need a strong reason to always motivate me. You can see my notion on Fig 1. My reasons are personal so you can’t see it haha, but the point is, I have to find “my reasons”, I mean really strong why.
After that, I chose some resources to guide me learn data science and also the timeline. On average, I spend 2–3 hours every day learning data science. When you create a timeline, your learning process will be measurable and you will clearly know your learning progress. For some reason, it gives pleasure and increases my dopamine hormone. I became more consistent. I recommend using Notion because it’s really fun.
I learned from youtube (codebasics, Alex The analyst, Ken Jee, Tina Huang, etc), books (Data Storytelling, Statistics, and Problem Solving 101,etc) online courses (DQLab, LinkedIn Learning, Coursera,etc) and some articles on medium and LinkedIn. I applied financial aid for Google Data Analytics course in Coursera and I use my free trial premium LinkedIn to enjoy courses on LinkedIn for one month.
The problems is too much informations, super overwhelming! A lot of free information on the internet. I make some rules, I just have to choose maximum 3–5 resources and then start learning. Don’t be too overwhelming in having resources. I don’t recommend only 1 resource because later the information obtained may not be too complete and can also be biased.
2. Finished #66DaysOfDataChallenge
This challenge was made by Ken Jee, one of the best youtube channels about data science. I started to join this challenge Dec 2021 and I have to post all my learning journeys on Twitter. According to James Clear by his book Atomic Habits, he said on average, it takes 66 days to build new habits so a new behavior become automatic. Some benefits that I got when I join this challenge such as building daily learning habits, get comfortable sharing my work, and accountability.
There’s nothing more frustrating than learning something from someone who hasn’t done what he’s talking about, but Ken Jee did it and it makes me want to be part of his community.
I totally agree we have to build daily learning habits because of momentum and tipping point. But, I don’t get anything in five minutes learn data, I can understand and get the point min spend 30 minutes. I think we have to put some effort and focus, and I don’t think we can get both by 5 minutes. I totally understand why 5 minutes because we can likely do no matter what the circumstances are. The challenge of building habit is about consistency and not about how many hours we can put it. But, it doesn’t work for me, maybe for you guys work. Go for it.
For the first time I learned data, I don’t have courage to share it on social media but after finished this challenge, I’m no longer the same person. I see so many people out there join these challenges and share their work on Twitter. I felt, I have some friends. If you guys want to learn data but feel alone, try this challenge.
3. Deliberate Practice
One month after decide to learn data science, I got an internship in the know your customer (KYC) division. I can stop to learn data science right? But no! Even though my jobs are not related to data science, I always learn. In my free time or weekend, I spend my day learning data, watching webinar, doing some projects, practicing my coding (SQL) and keep it for myself.
3 months later, my internship finished, I was accepted to be full time in the same position. Somehow I was curious about the data team at my company, I have the courage to ask the data team (staff, lead, and even head of data). I did 1 on 1 meetings with different people (total three meetings). I felt really brave to start a conversation with random people and ask them to meetings. But all my questions are finally answered during meetings. :”)
They may see my grit, ambition, passion, and interest in this field so they tried to offer me a position in business intelligence. I received a technical test (SQL and Tableau). Imagine, when I didn’t study months ago, would I be able to do this technical test? At that moment I believe luck is preparation meets opportunity.
They need someone in that position and I really want a career in data because I’ve been studying for months. After going through various processes, I was finally accepted to move the division to the data team in the same company where I did my internship.
The key is deliberate practice, wherever whenever and however when you have time, just try to learn something and practice. We never know what moment will bring us with our knowledge and skills we have. For sure, There are always challenges, whether it’s with building a strong career or learn something, but the one constant is that you never stop learning. Deliberate Practice.
And that’s my story of how I challenge myself to learn data science (as self-taught). I hope you enjoyed it as much as I did. Please let me know if you have any questions! You can either leave a comment here or on Linkedin (Let’s connect!) :)