Today’s post comes from Data Analyst student Christian Strobl, a former lawyer turned startup cofounder, currently living in Munich and learning data science within the Data Analyst Nanodegree. Read on to see how Christian made the big career shift outside of the world of law.

01In 2007 when I started in law school, it felt like a different time. I was looking for career security and was always interested in social science, literature, and ultimately doing something with words. The world was so insecure with the impending financial crisis, and I figured I would choose a path that guaranteed the most financial stability. I figured that if I worked hard in law school, I could be successful, have a stable path, and earn a good salary that would lead to a safe career path. That was the main inspiration and thinking behind attending law school.

In 2013 after my first law exam, I was working in a big firm in Frankfurt. I loved my boss and worked with a great team, but I couldn’t help feeling unfulfilled by my job. At about the same time, a friend of mine knew that I was very interested in technology and always reading up on tech blogs, so he invited me to attend a hackathon in Berlin. So I did, and even though I didn’t know how to code, it was still such a great experience. While I was there, I met someone that pointed me in the direction of online courses to start learning how to program. Later that year, I started taking courses online and quit law shortly after. I haven’t looked back.

When I was just 11 or 12 years old, I was always playing around with computers. I experimented with HTML, CSS, and Flash…mostly little kid stuff at the time. But over the years, I got interested in things outside of technology. So when I came back to the world of programming many years later, there was so much more to explore, including many new programming languages. Everything was way more advanced and you could do all these amazing new things.

Later that year, I started taking courses online and quit law shortly after. I haven’t looked back. tweet

The first time I heard about Udacity was in a newspaper article. I read about Sebastian and signed up for a Udacity course, and actually attended one of the first global Udacity events located at Google in Munich. But I didn’t start taking Udacity courses for quite a while. Early on I was refreshing the basics with Team Treehouse; I learned the basics of Ruby, Objective-C, and Python.

Fast forward to this year…I signed up for the Data Analyst Nanodegree when it was first announced. The main appeal to me is that I wanted to lose the fear of data science. Even though I don’t have a PhD, I could still jump in and understand the basics of data science. Right now I’m getting close to the halfway point, but on one hand, I already have so much less fear of data analysis. If I see a Python library, I am actually reading the documentation and not feeling like it’s too difficult. I feel a lot of improvement from that aspect, like the concepts are within my grasp and understandable. I can understand APIs to understand questions.

My biggest issue so far is that because project grading is almost instantaneous, there’s no break between courses and projects. So it’s difficult to get the motivation to continue on the next course and project right away. I need little breaks to stay motivated.

…I already have so much less fear of data analysis. tweet

The first couple Nanodegree projects have definitely been difficult without much instant gratification. You really have to read and research. Specifically for me, not having a statistics background meant that I had to pay attention and do my research to get a solid grasp on the concepts. If you take the time, you’re going to understand the concepts. It’s about motivating yourself to understand the right things. For example, during law school, it’s a lot of studying to understand the concepts. So if you’re not used to putting in the work, it might seem difficult especially on a track like data science.

I believe making projects you can be proud of is extremely helpful, and even though you might forget some of what you learned, you can always go back to the documentation and figure out what you need to accomplish. When I completed a Nanodegree project, I felt proud—like I accomplished something. It’s incredibly useful for data science because it’s a different discipline that pure coding.

From a professional point of view, I’m working on a startup in the hackathon industry. So the Data Analyst Nanodegree is becoming a huge help for learning how to properly aggregate and analyze data. Learning how to work with different APIs and databases is keeping me motivating—everything I learn in the Nanodegree, I can apply to what I’m doing in the ongoing process of building a better project.

…when I completed a Nanodegree project, I feel proud— like I’ve accomplished something. tweet

I also just know that data will be super important in careers of the future, especially in Germany. Having a basic education in data is going to be a plus in any field, and the Nanodegree is a great starting point in the greater field of data science.

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