How to Get Started in Data Science

How to Get Started in Data Science

Data Science is a field that I have found interesting for a while now. However, aside from spending hours reading about data science and what data scientists do, I never really went beyond that. During that period of research, one thing that fascinated me about data science the most is the ability to derive actionable insights from complex datasets that helps to solve real problems. That got me started, and hooked!

Navigating the data science landscape has brought me to the realization that everything one needs to get started in data science can be found online. In my case, I took courses on websites like freeCodeCamp, DataCamp, and O’Reilly, and worked on projects. I also signed up for a Data Science Bootcamp with Practicum.

I am currently a Data Scientist and Program Manager at Microsoft and today, I will like to share 10 tips that can help you get started in data science:
  1. You can find all the learning resources to get started with data science online and mostly for free on websites like freeCodeCamp, DataCamp, Codecademy, Coursera, Udemy, etc.
  2. Sharpen your technical skills and go deep, be it Python or R and SQL. Build your skills in Data Science using a language of your choice - You could explore more languages if needed once you’re well versed with your chosen language.
  3. Even if you’re not from a Math background, a foundational course in Mathematics and Statistics will go a long way.
  4. Remember that data science is more of a tool so have an understanding of the business problem you’re trying to solve using data science so that your solution aligns with the business objectives.
  5. Build projects for your portfolio. You can also create your own projects by going onto platforms like Kaggle and finding datasets with suggested use cases.
  6. Soft skills like communication, collaboration and empathy are very important as a data scientist.
  7. If possible, do at least one data science internship. This really helps in giving you an industrial perspective to how data science can be applied.
  8. Network with other data scientists (peers and mentors) on platforms like LinkedIn, Reddit and Kaggle.
  9. Join hackathons like the Kaggle 30 Days of ML and attend data science conferences and meetups; there are many online events happening every week on Eventbrite, LinkedIn events and Meetup.
  10. Don’t remain stuck on a problem for too long. Your roadblock may not be unique and there may be several available solutions online. Google and Stack Overflow are your friends.

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