2018: The year of Speedstudy
How much of Data Science can I master in one year ?
Until last year, I associated learning with school or University where we were given a curriculum and had to strictly follow a prescribed syllabus. That’s how education is in India. After graduating and working as a researcher for over a year, I was exposed to the wonderful open source community and a plethora of paid and free online courses. 2017 was the year when I started self-learning web development through free resources like FreeCodeCamp, Chingu cohorts and p1xt’s guides. Challenges such as 100DaysOfCode, DailyCSSImages and online collaboration projects in Chingu cohorts helped me gain confidence and build my portfolio. I also gained courage to write about what I learnt.
By the end of 2017, I learnt how to build full stack websites using Javascript. I read a lot of technical books, articles and tutorials and even published short tutorials on web development and data visualisation. I am surprised that I came this far in my self-learning journey. Even though I made good progress, there were some shortcomings. Last year I wasted a significant amount of time searching for what to learn (Javascript / Python / PHP / C++ ? ), watching quick tutorials, freebies and shortcuts instead of focusing on a single path.
This year I have decided to double my efforts and seriousness to learn Python and Data Science. Inspired by P1xt’s Speedstudy post, I have combined her Data Science +Python guides into a single progress tracking repo to track my goals for this year. I will also continue to write whenever I complete a course, a book or a project.
I challenge myself this year to complete all the courses and books in the Speedstudy repo, participate in Data Science competitions and publish significant results. I also invite others who share my goals to join me! :-)
