Generally you’ll start as a data engineer (read ‘person who uses code to organise data’) or data analyst (spreadsheets and business’) rather than a data scientist (read commercial statistician). If you’re starting from zero, it’s worth learning to code regardless, and if you love math then it’s plausible that data engineer could be a better entry point than web development. Pay is similar.
Ryan is a more experienced programmer/coder than I am. As a time-poor beginner, I found the MITx course on R much, much easier to use (and far more interesting) than the John Hopkins courses on Coursera. They also have two decent courses on Python, the second of which is more relevant to statistical applications.
I would believe that there are much better R courses than the Johns Hopkins one for an introduction. I’m not particularly experienced at coding, but I was basically only watching those videos for the stats, rather than paying much attention to the code at all. I agree that the mitx Python courses look decently good and wuantitative (though not mostly statistical) for an absolute beginner. The other thing is to try Kaggle introductory challenges in Python for a practical taste!
Generally you’ll start as a data engineer (read ‘person who uses code to organise data’) or data analyst (spreadsheets and business’) rather than a data scientist (read commercial statistician). If you’re starting from zero, it’s worth learning to code regardless, and if you love math then it’s plausible that data engineer could be a better entry point than web development. Pay is similar.
Thanks, Ryan. Do you have a specific starting recommendation?
i.e. best starting point if you think data engineering will suit you more than web development? (e.g. learn python)
Or quickest way to test out if you’re going to like the data science track? (e.g. start with a stats course rather than the coding)
Ryan is a more experienced programmer/coder than I am. As a time-poor beginner, I found the MITx course on R much, much easier to use (and far more interesting) than the John Hopkins courses on Coursera. They also have two decent courses on Python, the second of which is more relevant to statistical applications.
MITx course on R—https://www.edx.org/course/analytics-edge-mitx-15-071x-0 MITx course(s) on Python—https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-0 https://www.edx.org/course/introduction-computational-thinking-data-mitx-6-00-2x-0
I would believe that there are much better R courses than the Johns Hopkins one for an introduction. I’m not particularly experienced at coding, but I was basically only watching those videos for the stats, rather than paying much attention to the code at all. I agree that the mitx Python courses look decently good and wuantitative (though not mostly statistical) for an absolute beginner. The other thing is to try Kaggle introductory challenges in Python for a practical taste!
If you want to use Python (which would be nice, although most data courses are in R), then this looks good and practical: https://www.udacity.com/course/intro-to-data-science—ud359.
If you are happy to use R (a less generally useful language), then I can vouch for John’s Hopkins’ Courses courses being very good:https://www.coursera.org/specialization/jhudatascience/1.