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R Programming for Data Science

Basics of R programming as a preliminary step to become a Data Scientist

Course Description

This course provides an overview of Data Science and how R language with its methods and functions constitutes a primary tool to become a Data Scientist. The course presents an introduction to Data Science and Big Data. Then, it gives an overview of R and RStudio software and how to set them up. Lastly, it explains in detail, with the aid of numerous exercises, how to use various R methods and functions to analyze data.

The course demonstrates the importance and advantages of R language as a start, then it presents topics on R data types, variable assignment, arithmetic operations, vectors, matrices, factors, data frames and lists. Besides, it includes topics on operators, conditionals, loops, functions, and packages. It also covers regular expressions, getting and cleaning data, plotting, and data manipulation using the dplyr package.

The ever-increasing size of data globally coupled with the prominent need to extract insightful information out of it necessitate learning analytical programming languages such as R. This course paves the road for beginners to start using R in real life analysis tasks and research projects to enable a fact-based decision-making process.

Goals

Having completed this course, you will be able to:

  • Describe Data Science and Big Data
  • Recognize the importance of Data Science
  • Explain the Data Science process
  • Identify main tools used in Data Science
  • Explain the steps of a Data Science project
  • Recognize the main environment and files of RStudio
  • Complete installing R and R Studio on own machine
  • Solve arithmetic calculations in R
  • Distinguish between different data types in R
  • Solve data problems using vectors, matrices, factors, data frames, and lists in R
  • Formulate controlled-flow data problems using Operators, Conditional Statements, and Loops
  • Recognize base R functions and user-defined functions in R
  • Analyze data using base mathematical functions, R Packages, and Apply function family
  • Modify data using Regular Expressions and Dates & Times functions
  • Integrate and cleanse external data in R
  • Plot data in R
  • Evaluate datasets in R using dplyr package

Prerequisites

  • No prior knowledge is mandatory to this course.

  • Passion towards learning programming and statistics is essential

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Curriculum

  • About this section
  • Introduction to Data Science
    00:35
    Preview
  • Data Science: Career of the Future
    03:42
    Preview
  • What is Data Science?
    02:00
  • Data Science as a Process
    02:14
  • Data Science Toolbox
    03:25
  • Data Science Process Explained
    05:21
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R Programming for Data Science
This Course Includes
  • 6 hours
  • 133 Lectures
  • 25 Resources
  • Completion Certificate Sample Certificate
  • Lifetime Access Yes
  • Language English
  • 30-Days Money Back Guarantee

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