Learning data science is hard but I’ve found it to be incredibly rewarding. In this post, we'll give advice for aspiring data scientists...
Around once a month, I get emailed by a student of some type asking how to get into Data Science, I’ve answered it enough that I decided to write it out here so I can link people to it. So if you’re one of those students, welcome!
I’ll segment this into basic advice, which can be found quite easily if you just google ‘how to get into data science’ and advice that is less common, but advice that I’ve found very useful over the years. I’ll start with the latter, and move on to basic advice. Obviously take this with a grain of salt as all advice comes with a bit of survivorship bias.
If you’re at a university, half the point of being there is to find smart, ambitious, and motivated people like yourself to learn and grow with. For my alma mater, that community was the Data Science and Informatics club. Communities/networks help you get started, keep you motivated, and are key for scoring internships and full time offers in the long term.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
In this article, I will present the 22 questions in fundamental statistics that you may encounter during interviews.
Need a data set to practice with? Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.
Five Books that Aspiring Data Scientists Should Read:Data science is not just about mathematics, statistics, and coding. It is about telling a great story.
Statistics for Data Science and Machine Learning Engineer. I’ll try to teach you just enough to be dangerous, and pique your interest just enough that you’ll go off and learn more.