I know there are many people starting out in data science who just don’t know where to start in the huge variety of topics under the umbrella of data science. You may be one of those beginners, wanting to participate in the Summer of Data Science #SoDS17, and not knowing what goals to even set.
One suggestion to get started learning if you’re starting from scratch is to pick a book or a course, and set a goal to complete and understand the content in that book or course. NOTE: the one you pick first may not “speak to you”, and you may need additional online resources or other books that explain a topic just slightly differently so it clicks for you. So don’t get discouraged when you don’t “get it” from one resource!
Here’s a talk I gave at PyData 2016 about how to get started learning, with advice from my podcast guests.
And below are a whole bunch of resources on DataSciGuide to choose from to get started!
- Doing Data Science by Cathy O’Neil and Rachel Schutt
- Data Scientists at Work by Sebastian Gutierrez
- Storytelling with Data by Cole Nussbaumer Knaflic
- Books by Stephen Few on Visualization
- Naked Statistics by Charles Wheelan
- Data Smart by John Foreman (uses Excel)
- The Art of Data Science by Roger Peng & Elizabeth Matsui
- The Data Science Handbook by Various
- Practical Data Science with R by Nina Zumel and John Mount
- Learn Python the Hard Way by Zed Shaw (also includes videos/website)
- Other Books
- Courses and Programs
- Even more beginner-friendly resources (scroll down and choose categories/tags from the dropdown to filter further)
Once you use any of these resources, please add your own rating, to help other people find experience-level-appropriate data science learning content!
If you have a favorite resource that helped you as a beginner that is not on DataSciGuide yet, please email me at firstname.lastname@example.org and I can add it so you can review it.