Want to pick up data science? Brush up on your math first
It's easy to get lost looking for an introductory course to online. There are thousands of courses, and tens of open courseware websites. So we composed a minimalist list of introductory statistics courses that you can take with little to no previous knowledge. The courses are on-demand every few months and are substantial in content. They're interactive so you don't need any books or read-only tutorials, and get teach through coding up examples, i.e. R or Python. Let's dig in.
1. Foundations of data analysis on edX
This two-part series (Part 1 covers Statistics using R and Part 2 teaches Inferential Statistics) is one of the top reviewed statistics courses available, with a weighted average rating of 4.48 out of 5 stars. This is one of the few courses with high ratings that teaches statistics with a focus on coding up examples. It also covers a lot of probability content, and is a great mix of fundamentals for the beginner data scientist.
Estimated duration: 6 weeks at 3-6 hours per week for each course
2. Introduction to probability—The science of uncertainty on edX
With a rating of 4.91 out of 5 stars, if you want to dive deeper into the world of probability, this is the course for you. Don't let its name fool you, this course is a challenge and much longer than most online courses. While the level at which the e-course covers probability is not necessary a beginner data scientist, the contents are essentially the same as the corresponding courses taught in MIT over the past 50 years, and teach probabilistic models, inference methods, random processes, and more. Added bonus: The teachers are both professors in the Department of Electrical Engineering and Computer Science at MIT!
Estimated duration: 18 weeks at 12 hours per week
3. I "heart" stats: Learning to love statistics on edX
With no coding involved, University of Notre Dame's intro to stat course targets a non-technical audience, making it good for anybody. The course design and instructors are fun, using entertaining examples related to real-life situations we all encounter in everyday life. The professors quip, "If you can add, subtract, multiply, and divide (or just be able to use a calculator to do that!), you will be more than able to handle what will happen as this relationship develops."
By the end of the course, students are promised to be able to identify the most important features of a data set, select statistical tests, think like a detective, and understand the relationship between different variables.
Estimated duration: 9 weeks at 4-6 hours per week
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