Serhan Tanriverdi

Serhan Tanriverdi, a data analytics expert at the US-based career coaching company Bravely, talks about the ups and downs of starting out as a complete beginner with non-quantitative background, and how 365 Data Science helped him transition from academia to his first steady employment in the field.

Became a Data Analyst Without a STEM Degree

Serhan Tanriverdi proves that a quantitative degree is not a prerequisite for a successful career in data science. Currently working as a full-time data analyst in the US, he started his journey into the field just a year ago with a Ph.D. in Sociology and no relevant experience.
“Although I have a successful academic career in my domain focusing on qualitative social sciences, I started to realize the increasing significance of data science both in academia and the corporate world, and I wanted to specialize in this domain.”, Serhan explains.

365 Data Science allowed me to gain the necessary knowledge and experience without having to do a Master's or a Doctorate in data science.

Before joining our program, Serhan tried several well-known e-learning platforms for data science. However, he was disappointed that most courses were either too short and superficial, or they were detailed to the point where he was left confused. He had a hard time finding in-depth and comprehensive courses that also consistently showed the big picture necessary for data analysis.
After reviewing and comparing many platforms, his search for the ideal data analytics training led him to 365 Data Science.

In 365, it is possible to find both beginner and advanced education together. The 365 instructors successfully teach the basic skills you need to start your entry-level data analysis career. At the same time, you can specialize in different fields of data science and expand your career opportunities.

Serhan describes the systematic training as very helpful. Having started from scratch, the structured modules prevented him from losing his way within the complex world of data analytics.

This training provides a very good roadmap for first-time learners. In addition, the Q&A hub allows you to find answers to the potential questions you might encounter during your study. So, you could study at your own pace, without a teacher. The community and instructors are very supportive in the Q&A hub.

Another thing Serhan liked about the platform is the wide range of detailed lessons on different subjects and the step-by-step preparation of projects - in his words, a great opportunity for candidates who have difficulties in creating their portfolios for job applications.

The most important stage comes after completing the courses, and 365 Data Science provides many resources and personalized feedback with very useful advice on the job search process and portfolio preparation. In short, 365 provides the A-to-Z in data science training.

The result?
Serhan believes the knowledge and experience he gained from 365 Data Science has made his life easier and exciting in many practical areas. He applied his knowledge of Excel formulas in his personal financial planning; he also began writing machine learning models and started doing statistical analysis using Python. And with his newly acquired Tableau skills, he was finally able to visualize and share his research results with others in an engaging way.

But the biggest benefit of 365 Data Science was that I managed to land a full-time job as a data analyst. I ended up receiving offers from technology companies while continuing my academic career in social sciences. In this respect, 365 has provided a great career development opportunity for me.

While Serhan has already completed many courses in 365 Data Science, he is looking forward to expanding his skillset with more upcoming additions to the program.
His own experience taught him that a STEM degree is not the only gateway into data science and analytics. He is happy to see that the popularity of data analytics jobs is rising because they are future-oriented, very relevant for today’s complex world, and financially rewarding.
However, seeing that most aspiring data professionals feel intimidated about entering this field, he offers some words of encouragement.

Most people think that to be successful, it is necessary to have a mathematics, engineering, or computer science background. But this is a very incomplete thought. A lot of accomplished people in this domain come from non-STEM fields. I am one of the examples. Although I completed my undergraduate and graduate education in social sciences, I saw that it is possible to learn data science with good motivation, disciplined work, and the right mindset without a STEM degree.