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Learn R Basics with a (FREE) Top Data Science MOOC from Harvard on edX


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Data Science: R Basics
Provided by Harvard University (HarvardX)
Build a foundation in R and learn how to wrangle, analyze, and visualize data.
  • Cost: Free
  • Upgrade: $49 USD
  • Commitment: 1–2 hours per week, for 8 weeks
  • Level: Introductory
What You Will Learn
  • Basic R syntax
  • Foundational R programming concepts such as data types, vectors arithmetic, and indexing
  • How to perform operations in R including sorting, data wrangling using dplyr, and making plots
Data Science: R Basics is the first course in Harvard's Professional Certificate Program in Data Science. To help learners grasp the concepts of R programming, the course focuses on teaching the R skills needed to solve a specific problem using a real-world dataset about crime in the United States.

You will learn R's functions and data types as well as how to operate on vectors and when to use advanced functions such as sorting. General programming features like “if-else,” and “for loop” commands, and how to wrangle, analyze and visualize data are also covered.

This is an introductory course which will give you a strong foundation to prepare you for the more in-depth courses later in the series which cover more in-depth concepts.

An up-to-date browser is recommended to enable programming directly in a browser-based interface.

Course Format
  • Self-Paced: course contains assignments without due dates. You can progress through the course at your own speed.
  • Course ends: Jun 29, 2019
Meet the Instructor, Rafael Irizarry
Rafael Irizarry is a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health and a Professor of Biostatistics and Computational Biology at the Dana Farber Cancer Institute. For the past 15 years, Dr. Irizarry’s research has focused on the analysis of genomics data. During this time, he has also has taught several classes, all related to applied statistics. Dr. Irizarry is one of the founders of the Bioconductor Project, an open source and open development software project for the analysis of genomic data. His publications related to these topics have been highly cited and his software implementations widely downloaded.

To enrol on this course, follow the link to the course page on edX: https://www.edx.org/course/r-basics-2

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Introduction to Programming

  1. Overview of R, R as calculator
  2. R data types and objects, functions, classes
  3. Control structures, Loop functions (if, else)
  4. Data Exploration functions in R (summary of data)
  5. How to import data from various sources like SQL, Excel, csv formats to R
  6. Visualization including Plots and Dashboards in R
  7. Data Manipulation in R
Statistics and Probability

  1. Foundation of Statistics
  • What is Statistics?
  • Population and Sample
  • Types of measurements / Data
  • Variables
  • Categorical and Quantitative Variables
  • Branches of Statistics
  • Descriptive Statistics
  • Inferential Statistics
  • Exercises and applications
  1. Descriptive Statistics
  • Introduction
  • Central Tendency
  • Measures of Central Tendency
  • Measures of Variation Dispersion
  • Measures of Position
  • Measures of Quality and Outliers
  • Exercises and applications
And more...