It seems like lots of people on LW want a slice of this “data science” pie that everyone keeps talking about. I know it’s a highly ambiguous buzzword at the moment, but what would be a good syllabus for these people?
I’m cobbling my own together at the moment, (mostly consisting of R, NumPy, lxml and a lot of extracurricular linear algebra), but it never hurts to have a bit of extra structure. What should prospective “data scientists” be learning, and where can they find it?
Whenever I see the phrase “data science” I remember Cosma Shalizi’s blogposts about data scientists being statisticians who can program and market themselves well. Maybe you can lift something from his stats department’s course list?
It seems like lots of people on LW want a slice of this “data science” pie that everyone keeps talking about. I know it’s a highly ambiguous buzzword at the moment, but what would be a good syllabus for these people?
I’m cobbling my own together at the moment, (mostly consisting of R, NumPy, lxml and a lot of extracurricular linear algebra), but it never hurts to have a bit of extra structure. What should prospective “data scientists” be learning, and where can they find it?
A tentative sequence for learning “data science” (inspired by Daniel_Burfoot):
Statistics One
Learn to Program: The Fundamentals
Learn SQL The Hard Way
Introduction to Data Science
Machine Learning
Computing for Data Analysis
matt of Conductrics put up a somewhat detailed blog post on learning data science.
SQL, machine learning, statistics, data visualization.
Whenever I see the phrase “data science” I remember Cosma Shalizi’s blog posts about data scientists being statisticians who can program and market themselves well. Maybe you can lift something from his stats department’s course list?