My Biggest Mistake in Data Science

Hello again! This blog post will be about probably my biggest mistake in my self-learning journey.

Let’s begin.

I started learning Python programming by myself almost 3 years ago. I was reading books, taking online courses, and consuming other educational content. Then I needed to choose a field to focus on deeply. I continued with Data Science because I have a big passion for Artificial Intelligence. I fell in love with AI in my childish time. Loved Tony’s conversation with Jarvis, a chatbot has cognition and all calculation power, just incredible to inspire people. Anyway, back to my mistake.

There are a lot of traps in the self-learning journey, one of them being which content you should consume. But, there are dozens of, thousands of courses out there, on the Internet. How to choose one? I also fell into this trap but that’s not my focus right now.

I’m talking about the balance between theoretical and practical knowledge. In the Data Science field, some people advocating to not learning Math at the beginning of the Journey, which is the Biggest Trap! I attended a lot of meetups both Academical and Industrial. I met a lot of people and learned a lot of things from them. In the Academical meetups, the conversation is always about how important Math and Statistics are in Data Science. Against this, my some feelings are saying the opposite. As a student, I said to myself that “I guess it’s not important right now, I would learn in the future, It’s probably not necessary for me, right now.” and I tricked myself and regret it every second right now. :/

It’s almost 2 years, in my data science self-education journey. I’m so sad to say it, but I started Math almost 2-3 weeks ago. Volkan Kumtepeli, one of the academical meetup speakers, always said that

Learn math! You can start with Linear Algebra. There are some fantastic courses on Linear Algebra by the world renowned MIT professor, Gilbert Strang. I am still watching his videos over and over again.

I didn’t understand that time, or maybe I just procrastinated on my math journey. I felt that lack of theoretical knowledge and started my journey. Copied the “Introduction to Linear Algebra” book on my birthday and started the MIT 18.06SC course. Reality-shifting and taking insights from people better than you are so important! It is one of the biggest turning points in my life. Thank you Volkan Kumtepeli and other people who advocate the importance of Math and Science.

Lastly, my biggest advice for people starting Data Science is that “Don’t Ignore the importance of Math!”, “Do not procrastinate in your Math Journey.”

About author 🧙‍♂ ️

I like communicating with people online and on social media as a self-taught machine learning engineer. Follow me to be my friend, and I look forward to engaging with you here or on other platforms! Long details of who I am may be found here!🔥

Some Resources for Math newbies;

MIT 18.06SC Linear Algebra Course:

Gilbert Strang Calculus Lectures:

MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning:

The Math Sorcerer Youtube Channel: