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The Data Scientist’s Toolbox (Coursera)

The Data Scientist’s Toolbox (Coursera)

Key Facts

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Provider
School
Language
Level
Coursera
Johns Hopkins University
English
Beginner

By enrolling in this online course you will spend approx. 4 Weeks/ 1-4 hours a week to learn key concept of Data Science.

Course Overview

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.

Course Syllabus

Data Science Fundamentals

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.

R and RStudio

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.

Version Control and GitHub

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.

R Markdown, Scientific Thinking, and Big Data

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.

Meet your Instructors

Jeff Leek

Jeff Leek is an Assistant Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and co-editor of the Simply Statistics Blog. He received his Ph.D. in Biostatistics from the University of Washington and is recognized for his contributions to genomic data analysis and statistical methods for personalized medicine. His data analyses have helped us understand the molecular mechanisms behind brain development, stem cell self-renewal, and the immune response to major blunt force trauma. His work has appeared in the top scientific and medical journals Nature, Proceedings of the National Academy of Sciences, Genome Biology, and PLoS Medicine. He created Data Analysis as a component of the year-long statistical methods core sequence for Biostatistics students at Johns Hopkins. The course has won a teaching excellence award, voted on by the students at Johns Hopkins, every year Dr. Leek has taught the course.

* We try to provide you as many free online courses from multiple providers and universities but in some cases you may have pay nominal fee to get assignments and/or to claim verified Certificate or Degree from respective provider.

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