Complete Data Science Career Roadmap for Non-Majors

A Data Science Roadmap from a Non-Major 🚗

Are you a non-major or have no background in data science, but still want to enter a data science career? This course is for you. This course is a data science roadmap that provides study methods and direction for non-majors to become data scientists.

As a non-major with a liberal arts background, I successfully transitioned to a career in data science and currently work as a data scientist in the UK. Recently, I've been building my data science career by running a YouTube channel and working on data science projects. While data science can be a daunting field, I'll share practical tips on how to effectively embark on a data science career.

My lectures are an investment that will eliminate wasted time and effort. By following the lectures closely, you'll learn what I've learned through trial and error, allowing you to enter data science more effectively and quickly.

Lecture Features 🚩

As someone who didn't major in data science, I understand better than anyone the frustrations, difficulties, worries, and concerns that come with preparing for a career in data science. Based on my own experiences and lessons learned through trial and error, I'll share practical methods to help you shorten your career preparation time and optimize the process.

Are you wondering if you can do it even though you're not a data science major? Regardless of your major or background, anyone can create a roadmap for a data science career that's right for them.

At the end of each chapter, we provide practice problems that allow you to apply the lecture content to your own situations. Solving these problems will give you the opportunity to reflect on what you've learned and find the right answers for you. These practice problems also provide specific examples based on my own experiences, allowing you to apply what you've learned.

Introduction by section 📖

• Can a non-major become a data scientist?

Learn why your major is advantageous for a data science career and use it to create a unique selling point that can be leveraged to your advantage during the job search process.

• Understanding Data Science Careers

Understand data science and its career paths, and set goals for a data science career that fits your background and circumstances.

• Start preparing for a data science career

Identify the skills needed to achieve your set goals.

• How to Study to Perfect Your Data Science Career Skill Set

Learn how to study and develop a plan to develop the skills you need.

Lecture Review 🌹

Expected Questions Q&A 👨‍🏫

🙋‍♂️ Can non-majors also take the course?

A-1. Yes. My lecture is for those who want to enter a data science career without any prior data science background. Even those with prior data science knowledge who are unsure of how to begin preparing for a data science career can take my lecture and effectively prepare for their career.

🙋‍♂️ Is there anything I need to prepare before attending the lecture?

A-2. While there's no need to prepare in advance, a proactive approach is essential to effectively utilize the lectures. By solving the practice problems I provide for each chapter, you'll not just passively listen to the lectures, but also reflect on what you've learned. Apply the practice problems to your own situation, find the right answers, and you'll develop a roadmap tailored to your needs.

🙋‍♂️ What are the benefits of taking this course?

A-3. Based on my own experience as a non-major, I've realized that those who take this course can optimize their career preparation time and process.

I currently work as a data scientist in the UK. Before coming here, I completed my undergraduate and master's studies at Korea University. Personally, I run the data science project "Visualizing Korea (https://visualisingkorea.com)." In 2020, Visualizing Korea won first place in Deacon's "COVID-19 Data Visualization AI Competition," often called the Korean Kaggle. In 2019, an article published by Visualizing Korea was also a finalist for the Data Journalism Awards' Data Visualization of the Year award.

Although I am currently actively working in the field of data science and even run a YouTube channel about data science (https://www.youtube.com/c/visualisingkorea), five years ago I was a non-major with a liberal arts degree preparing for a career in data science.

Having been a non-major myself, I understand the frustrations and concerns that come with preparing for a career as a non-major. To help you avoid wasting time like I did and maximize your preparation time, I've shared my insights from trial and error as a non-major, the things I wish I'd known earlier in my career in data science, and, most importantly, the things I wish I'd known when preparing. I'll share all of these insights with those who are at the same crossroads.

Even if you're a complete beginner or non-major in data science, I hope you'll follow my lectures carefully and learn how to effectively prepare for a data science career without wasting time or effort, unlike me who wasted time and missed many opportunities.