Learning data science (or data analysis) is a complex task that has lots of small, achievable sub-goals. Each person’s way of working through these small skill acquisition journeys will be different, and not every person has to learn every skill.
Still, here are some simple ways to consider getting started.
Are you an Excel user who wants to step up your game? Learn more about why we have concerns about Excel, and ways to mitigate risk in our article about Excel caveats and this article by converted Excel user Rich Hanna.
Are you curious about R and Python? Not sure what these tools accomplish that your other tools don’t? See them in action in our “beginners labs”, where you can be hands-on and try code, or simply play the video to watch data analysis unfold in real time. Try the one for R or the Python version
Why are R and Python getting all the attention? What about SAS, SPSS, Stata, and other perfectly adequate tools that you’ve used for years? Consider reading about scripted analysis, literate statistical programming or the “why” of literate statistical programming
Looking for community? We can help! Learn about user groups at CHOP, sign up for CHOP’s R User Group, or ask for an educational consult by emailing email@example.com.
Once you’ve begun to scratch the surface, it makes sense to learn more specific skills related to your work. To do that, please browse our education materials!