Read how the author used their time to level up a variety of their data science skills over a short period of time, and learn how you could do the same.
March 2020, I received a call informing me that I would be furloughed until further notice — informally meaning I’d be paid to learn. I knew the probability of me being made redundant after the furlough period ended was high since there were no projects I was actively working on.
Even though I hadn’t been doing much work with data at work, the thought of not being able to do any meaningful work with data bothered me. Nonetheless, I felt like my options regarding what I could possibly do next were limited since I did not get much practical experience at work. Don’t misunderstand me, I had been doing work as an intern, but I hadn’t done anything to significantly (or even marginally) improve the business (at least in my eyes) in my time. I was in a very low place, lacking self-belief, doubting my skills… For me, the furlough couldn’t come sooner.
The first transformative decision I made was to commit to becoming a future-proof indespensible Data Scientist.
When you make a commitment to do something, a force from within drives you. I wake up every day thinking I must be better today than I was yesterday and that is what drives me. However, for this post, I am going to share the 3 things I did during my furlough period to ensure that I move closer to my goal.
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.
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.
These data science tools illustrated guides are broken up into four distinct categories: data retrieval, data manipulation, data visualization, and engineering tips. Both online and PDF versions of these guides are available.
Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.