Summary

The author describes their personal journey of becoming a self-taught data scientist through online courses, hackathons, personal projects, and ultimately securing a job in the field without a formal degree in data science.

Abstract

The author, a self-taught data scientist with a background in economics, shares their story of breaking into the data science industry. Initially facing a lack of job opportunities in their field of study, they turned to self-education, starting with over 30 online courses from platforms like Coursera and edX, including classes from industry giants like Microsoft and IBM. The author emphasizes the importance of hands-on experience gained from participating in hackathons and working on personal projects, which not only built their portfolio but also provided insights into real-world industry problems. This self-directed learning led to their first data science job within a year and eventually to a successful career with an international consulting firm. The author advocates for the possibility of entering the data science field without a degree, stressing the value of self-motivation, problem-solving skills, and community support.

Opinions

The author believes that formal education in data science is not a strict prerequisite for entering the field.
They value the learning opportunities provided by online courses, especially those with industry relevance.
Engaging with a community of peers and mentors through forums and hackathons is seen as crucial for growth and networking.
Personal projects are considered essential for applying theoretical knowledge to practical problems and for showcasing skills to potential employers.
The author suggests that persistence and self-motivation are key components in the journey to becoming a data scientist.
They encourage individuals in similar situations to pursue data science by leveraging the abundance of available learning resources and community support.

How I Became an Actual Self-Taught Data Scientist: My Story

My journey from having no experience in data science to being in the industry for 5 years now

I am a self-taught data scientist who has been working in the technology industry for 5 years.

I was always interested in programming, but never had any formal training. My love of learning and curiosity about how things work led me to find ways of teaching myself new skills on my own time.

This blog post will discuss those paths that helped me become a self-taught data scientist!

I Didn’t Go to University for Data Science

You see I didn’t go to school for data science I went for economics and I wasn’t doing anything with that degree. So, when it came time for me to look at jobs I found there weren’t any opportunities in my field.

Now even though the job market was bad in general (at least where I lived), there were a lot of big data positions open but like many employers they wanted people with degrees or experience because nobody knew how much these roles would work in a company back then.

So with that in mind why would any employer bother taking a chance on someone without experience?

Even with this thought in mind I was still interested in learning the field so I started doing some machine learning on my own at the end of college. I loved learning about machine learning and I decided to take it seriously and get into data science more seriously.

So here’s how I did it…

I Took Over 30 Online Courses

I started with a few online courses that I found on coursera and edx. Coursera is great because they have a lot of data science specific classes from companies like Microsoft, IBM, Silicon Valley Data Science Academy (SVDSA), etc.

The SVDSA was the first class I took and it really got me interested in learning more about data science which has been my passion for quite some time now so naturally it made sense to take their course. It helped put me on track to be where I am today.

The other thing these courses do is give you access to forums where others involved in the field are available all over the world.

You can ask questions, get feedback and learn new things from people who are doing the same thing you’re trying to do.

These courses really helped me learn the fundamentals of data science and how to apply them. I was able to see what other people were working on, how they approached problems.

I Signed Up for Hackathons

After taking over 30 data science related courses I decided to start trying hackathons. Hackathons are events where you work on a project (data science related) with other people for about 24 hrs . You don’t sleep and the goal is to come up with something cool.

I found this was great because it helped me learn how to put all my new data science knowledge into practice as well as meet like minded individuals who were also interested in learning more about data science or had already learned quite a bit.

You see, hackathons aren’t just useful for meeting others they’re actually very helpful when it comes to building projects that could be used by companies which is what we want right?

So anytime someone else has an idea of some sort but doesn’t have time/resources to do anything about it I volunteer myself because I’m always looking for opportunities that might help me gain experience.

This is how I started working with companies on side projects which are really helpful because you get to work closely with people who are already in the field and they can give you great feedback, teach you new things or even mentor/sponsor your own project if it’s good enough.

I Did a Bunch of Personal Projects

I started doing projects for myself to help build up my portfolio. This way employers would know I was capable of learning new things on my own and that I had experience with machine learning or data science related topics even if I didn’t have a degree .

This also helped me learn more about real world problems as well as how people approach them which is something you don’t get from online courses because the whole point of those types of classes are to teach you what’s going on behind-the-scenes so it can be difficult sometimes when trying apply that knowledge in an actual scenario unless it’s just like the example given in class.

So, whenever there were any questions I couldn’t find answers for online instead of waiting around for someone else to do it for me I tried to find a way to do it myself. This was definitely difficult in the beginning but it got easier as time went on.

Now, I’m not saying online courses or hackathons are bad they’re actually great and really help you get started especially if you don’t know where to start but what I am saying is that doing personal projects can be extremely beneficial because you learn more about how to solve problems, how companies work and what they’re looking for.

My 1st Data Science job

After doing all of this for about 1 year or so, I applied for a big data position and got it!

The company was actually impressed with my self-taught skills and said they’ve never seen anything like that before.

The team was great, the work was interesting and my managers were very helpful when it came to teaching me new things or giving me feedback on my work.

Where I am now

Today, I work as a data scientist for an international consulting firm and was even recently named one of the top young professionals in my region.

I’m very thankful that I chose to follow this path because it allowed me to do things most people would never be able to experience but what’s really cool is that anyone can start doing something like this if they’re willing too.

There has been numerous times where I’ve thought “nobody is going to hire someone without a degree” but now looking back on everything it seems clear as day, you have to keep pushing yourself no matter how difficult or frustrating it might seem.

You Don’t Need a Degree to Be a Data Scientist

So if you’re in a similar situation as me, don’t worry. It’s definitely possible to become a data scientist without any formal education or experience.

The most important thing is that you have the drive to learn and are motivated to solve problems. And if you can find a mentor or community who can help guide and support your learning then that’s even better!

But don’t be afraid to start learning on your own either because there’s plenty of resources out there.

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