Introduction April is such a fantastic time of the year - the weather starts to warm up, trees and flowers start blooming, and many of us start in on some spring cleaning. So it’s only natural that we’d focus on the same thing in our R4DS Online Learning Community!
Finishing up March’s Viewing Parties Thank you to everyone who participated in our viewing party in early March, where member Chris B.
It always starts with a DM on Twitter, where someone shares with me their personal data science ambitions, where they currently are in their plans, and then they follow up with a request for me to help them figure out where to go next.
I love these messages—they’re an affirmation that the R community continues to grow and attract new members in part by creating a welcoming and supportive space for beginners, and that our community members are deemed approachable (enough) for someone brand new to R to reach out!
Background In August of 2017 I launched an experiment, referred to as the R for Data Science Online Learning Community, with the goal of creating a supportive and responsive online space for learners and mentors to gather and work through the R for Data Science text.
Like most online learning endeavors, we had a massive surge of interest at the onset, with exponential drop-offs week after week as we progressively worked through each chapter based on an established schedule.
Background It took me eight years to finish my undergraduate degree, not because I took a lot of time off to volunteer or travel the world, but because I dropped out twice (twice!) due to never having learned to learn in my K-12 days.
Looking at my academic performance in high school, I wasn’t the kid you would think would struggle with college. But if you scratched beneath the surface of the good grades, you’d see a student who put in very little effort beyond generally paying attention in class and completing homework assignments.
Introduction Every day I talk to individuals who are working in one field, but are interested in learning more about how and where to get started in data analysis either as a hobby, or as part of a broader career transition. While there are a myriad of options out there - from online bootcamps to self-guided study through various web platforms and textbooks - it can be daunting to start something like this on your own.