I'm thankful for this - I don't know Calc! I think you'll learn more useful skills and theory. Overall I'd recommend it if you're completely new to data science.

Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with.

This course will cover the basic ways that data can be obtained. The amount of time I dedicated to each course varied. Yes, you can access the course for free via www.coursera.org/jhu. Made a first step in the right direction and gained some foundational knowledge. Yes, you can take all 9 courses for free, do all the coursework and have some projects to show in your Github account. Offered by Johns Hopkins University. Begin by taking The Data Scientist's Toolbox and Introduction to R Programming, in order.

In terms of credibility for employment or school admissions, it's not worth much at all. So if you are unsure about buying this one on Coursera, get yourself some Udemy courses (since they are almost free) and get started already. Additional research - If you follow the content provided to the "T", you should be able to have enough to answer all quizzes and projects, right?

Navigate the entire data science pipeline from data acquisition to publication.

Demand for data scientists is racing ahead of supply. Use R to clean, analyze, and visualize data. If you only want to read and view the course content, you can audit the course for free.

The middle courses are a little slow (for me, anyway) because I'm already familiar with statistical inference.

It's pretty good stuff, but it is not without it's flaws. A bit of a personal preference but wish there could be a "textbook" option instead of videos.

This course covers the essential exploratory techniques for summarizing data.

In any case, I've found the specialization an excellent way of learning R. The math part of Data Science, not so much.

By using our Services or clicking I agree, you agree to our use of cookies. The StatInf class was particularly bad, and the RegMod course is much better, but both of them need work and serve best as refreshers, as opposed to introductions to the material. 16 comments. I am sharing this information with the hope someone might find it useful. What will I be able to do upon completing the Specialization? Wrong!

While others will find themselves struggling a lot with the content, delivery pace, quizzes and projects.

He uses phrases like 'this one' and 'that guy' and uses seemingly-interchangeable language on a whim, instead of precise language. Obviously, they [a recruiter] are going to ask you about it so it would probably help to have some example work of what you've done/learned. A ten-course introduction to data science, developed and taught by leading professors. This was particularly true during the Capstone Project.

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