Breaking into any new field or slogging through a career change is always a challenge, and requires focus and even a little grit. While transitioning to becoming a Data Scientist is no different, aspiring to this role is possible, even without a degree, largely due to the vast amount of quality learning resources available today.
Honing your data science skills
There are two main levels of data science skills that you want to hone – foundational and specialisation.
Data Science foundations
You want to start off with the basics. This is because building a strong foundation will make your data science journey a lot smoother. Particularly, we recommend that you build your fundamentals in the following topics: statistics & probability, mathematics, and programming.
Data Science specialisation
Once you’ve mastered the fundamentals, you’re ready to specialise. Yes, it’s finally the time you’re waiting for, the time to bring out all the programming languages you’ve been wanting to learn. Python, C++, you name it. At this point, it is also up to you whether you want to focus on machine learning algorithms, deep learning, natural language processing or computer vision. There are so many more things that you can specialise in, so please explore more before you make a decision!
Show off your data science skills
Learning data science is one thing, but why are you learning it? You can be proficient in it but no one else will know unless you market yourself. Something that people tend to forget. You want to show what you’ve learned and what you can do. This is especially important if you don’t have a data science related degree. Here are several ways for you to showcase them and market yourself:
First, you want to leverage your resume to showcase the data science courses you have taken, your proficiency in them and most importantly the projects you have created or partook. For this, we recommend creating a section called “Personal Projects” where you can list two to three projects that you’ve completed. Similarly, add these projects in the “Projects” section on your LinkedIn profile.
Another area you want to leverage to showcase your Data Science skills would be to create a Kaggle or Github repository if you haven’t already. Here, not only can you include all of your data science projects, you can also share your code with others to see. Once you have an active Kaggle or Github account, make sure that you share your account URL on your resume and LinkedIn profile!
Since we’re on the topic of how you can get into data science without a degree, you’d likely meet with obstacles while learning. So why not have help, and learn from the pros? Hackwagon offers courses for everyone, even if you’re a newbie in this area, like Data Science 101. What are you waiting for? Sign up for our next intake today!