7 Data Analysis Software Applications You Need to Know
December 15, 2024
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This course is part of multiple programs.
Instructors: Jeff Leek, PhD
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Set up R, R-Studio, Github and other useful tools
Understand the data, problems, and tools that data analysts use
Explain essential study design concepts
Create a Github repository
Add to your LinkedIn profile
21 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
In this module, we'll introduce and define data science and data itself. We'll also go over some of the resources that data scientists use to get help when they're stuck.
5 videos2 readings5 assignments5 plugins
In this module, we'll help you get up and running with both R and RStudio. Along the way, you'll learn some basics about both and why data scientists use them.
5 videos6 assignments5 plugins
During this module, you'll learn about version control and why it's so important to data scientists. You'll also learn how to use Git and GitHub to manage version control in data science projects.
4 videos5 assignments4 plugins
During this final module, you'll learn to use R Markdown and get an introduction to three concepts that are incredibly important to every successful data scientist: asking good questions, experimental design, and big data.
4 videos5 assignments1 peer review4 plugins
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
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Reviewed on Mar 11, 2020
I would like to thank Coursera and Johns Hopkins University for the course, I learned new things in the course which I think is the next step which can help me to accomplish my future goals.Thank you.
Reviewed on Oct 7, 2020
Great course content and very much informative with the different options of learning either through text or video. A good introductory course to the Data Science: Foundations Using R Specialization.
Reviewed on Jun 2, 2017
Nice Course. Basics are very well taught in this course.Thank you JHU and Coursera for this course. I have decided to donate 10% of my first salary to coursera once I am complete this and get intern.
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