My Journey into Data Science
Background and Family Perspective
I come from a family of lawyers, economists, doctors, and psychologists. Despite the intelligence of my mom and brother, I am convinced they have no idea what I do for a living.
Perceptions of Mathematics and Data Science
Paul Ernest from Exeter University said, “A widespread public image of mathematics is that it is difficult, cold, abstract, theoretical, ultra-rational, but important and largely masculine. It also has the image of being remote and inaccessible to all but a few super-intelligent beings with a ‘mathematical mind’… In contrast to the shame associated with illiteracy, innumeracy is almost a matter of pride among educated persons in Western anglophone countries.”
From my personal experience, it seems like everyone I meet has a tale about how terrible they are at statistics and how they cheated on all of their exams in college. It feels like it’s “cool” not to know mathematics. If you do know it, you’re probably seen as Sheldon from “The Big Bang Theory”—gifted in mathematics but portrayed as a lovable nerd. For many, this is what a data scientist looks like. While some laugh with these characters, many laugh at them, which isn’t helpful for our field.
Discovering and Growing in Data Science
When I began my journey in January, I never imagined I would love data science so much. I now realize that data science was designed for me. It is the profession I always dreamed of, but never knew existed. It combines elements of economics, mathematics, statistics, programming, marketing, and psychology. Besides that, I love writing technical content in data science and helping others. As my teacher Kirill Eremenko advised, it’s crucial to write about technical topics and Blockchain technology on your data science path.
My mentor Slavo suggested I might land a data science internship by June, but instead, I secured a Data Analyst position in February! It has been a crazy journey. I have worked on several projects using Tableau, Google Data Studio, Analytics, and more. Recently, I began using Python and am learning about ML, DL, AI, and Blockchain. I’m even developing my first Blockchain. A few days ago, I opened an Upwork account and immediately got a part-time job for a US company in data visualization.
Skills Development and Tutorials
I am learning Blockchain, SQL, Python for Data Science, and attending various bootcamps like “Machine Learning A-Z: Hands on Python & R in Data Science” and “Deep Learning A-Z: Hands on Artificial Neural Networks.” My mentor Slavo mentioned that everything before this was just warming up for the serious stuff. I have a set of tutorials that I need to complete by August 31st.
I’m using Tableau daily and striving to master it. Currently, my specialization is in Tableau. I am also going through these tutorials:
Future Plans and Contributions
I plan to open a Kaggle account and compete with other data scientists worldwide. Wish me luck! I’ve also joined Quora to answer data science questions and started my first YouTube channel. Next week, I will record my first tutorial on using Tableau and share my Data Science journey. Additionally, I’ve created a course called “Guerilla Marketing Masterclass,” the first of its kind in Serbia, focusing on guerrilla marketing and data science in marketing. While it’s still in its initial version, I’m working on version 2, which will be announced in September.
Philosophy and Learning Path
Why am I doing this? I believe the best way to master something is to learn theoretically, implement it in business, and share your knowledge with others.
Also, I’d like to present my wish list for after completing my current tutorials. This will be my path from September 1st:
P.S. I’m developing a website where you’ll find interesting content about Data Science and Blockchain. 🙂
