Introduction to R Programming for Data Science


Introduction

R is one of the best programming languages specifically designed for statistics and graphics. Programming in R is a fast and effective way to perform advanced data analyses and manipulations. In this course, you will learn how to use R and utilize the many data analysis techniques, methods, and functions it has to offer to the professional data scientist.

Duration

10 days

Target Group

Anyone interested in answering questions with data analysis, data visualization, and data science.

Course Objectives

  • Master the use of the R and RStudio interactive environment.
  • Expand R by installing R packages.
  • Explore and understand how to use the R documentation.
  • Read Structured Data into R from various sources.
  • Understand the different data types in R.
  • Understand the different data structures in R.

Course Outline

Introduction & Getting Started

  • Intro
  • Downloading and installing R & RStudio
  • Quick guide to the RStudio user interface
  • Changing the appearance in RStudio
  • Installing packages and using the library

The building blocks of R

  • Creating an object in R
  • Data types in R - Integers and doubles
  • Data types in R - Characters and logicals
  • Coercion rules in R
  • Functions in R
  • Functions and arguments
  • Building a function in R
  • Using the script vs. using the console

Vectors and vector operations

  • Intro
  • Introduction to vectors
  • Vector recycling
  • Naming a vector
  • Getting help with R
  • Slicing and indexing a vector

Matrices

  • Creating a matrix
  • Faster code: creating a matrix in a single line of code
  • Do matrices recycle?
  • Indexing an element from a matrix
  • Slicing a matrix
  • Matrix arithmetic
  • Matrix operations
  • Categorical data
  • Creating a factor in R
  • Lists in R

Fundamentals Of Programming With R

  • Relational Operators in R
  • Logical Operators in R
  • Logical Operators and Vectors
  • If, Else, Else-If Statements
  • If, Else, Else-If Keep-In-Minds
  • For Loops in R
  • While Loops in R
  • Repeat Loops in R
  • Building a Function in R 2.0
  • Scoping in R | Building a Function in R 2.0 (Ctnd)

Data frames

  • Creating a data frame
  • The Tidyverse package
  • Data import in R
  • Importing a CSV in R
  • Data export in R
  • Getting a sense of your data frame
  • Indexing and slicing a data frame in R
  • Extending a data frame in R
  • Dealing with missing data

Manipulating data

  • Intro
  • Data transformation with R - the Dplyr package - Part I
  • Data transformation with R - the Dplyr package - Part II
  • Sampling data with the Dplyr package
  • Using the pipe operator
  • Tidying your data - gather() and separate()
  • Tidying your data - unite() and spread()

Visualizing data

  • Intro to data visualization
  • Intro to ggplot2
  • Variables: revisited
  • Building a histogram with ggplot2
  • Building a bar chart with ggplot2
  • Building a box and whiskers plot with ggplot2
  • Building a scatterplot with ggplot2

Exploratory data analysis

  • Population vs. sample
  • Mean, median, mode
  • Skewness
  • Variance, standard deviation, and coefficient of variability
  • Covariance and correlation

Hypothesis Testing

  • Distributions
  • Standard Error and Confidence Intervals
  • Hypothesis Testing
  • Type I and Type II Errors
  • Test for the Mean. Population Variance Known
  • The P Value
  • Test for the Mean. Population Variance Unknown
  • Comparing Two Means. Dependent Samples
  • Comparing Two Means. Independent Samples

Linear Regression Analysis

  • The Linear Regression Model
  • Correlation vs. Regression
  • Geometrical Representation
  • Doing the Regression in R
  • How to Interpret the Regression Table
  • Decomposition of Variability
  • R-Squared

Enroll for this Course

We are proud to offer this course in a variety of training formats to suit your needs.

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Enroll to In-Person (Face to Face)

We use the highest quality learning facilities to make sure your experience is as comfortable as possible.

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Enroll for a Virtual Zoom Class

Join a scheduled class with a live instructor and other delegates.

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Enroll for Online Self-paced Class

Keep track of your own progression throughout your course and ensure continuous improvement.

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Benefits of Taking a Course at IRES

LEARN

Our courses are carefully curated to keep you abreast of latest industry trends, technological advancements, and best practices. We employ a variety of teaching methodologies, including hands-on workshops, case studies, and interactive sessions, all aimed at fostering an engaging and effective learning environment. Our expert instructors bring a wealth of knowledge and real-world experience, providing our clients with insights that can be immediately applied in their professional lives.

NETWORK

Our courses serve as a vibrant platform for professionals to connect and engage with a diverse community of peers, industry leaders, and experts. By participating in our programs, you gain access to an invaluable network that spans across various sectors and geographical boundaries. This networking aspect is not just about forming professional relationships; it's about creating a supportive ecosystem where ideas, opportunities, and collaborations can flourish.

GROW

Our courses are designed to challenge and inspire professionals to step out of their comfort zones and explore new horizons. Through a combination of theoretical knowledge and practical application, our programs help professionals refine their existing skills and acquire new ones, making them more versatile and competitive.

FAQs & Course Administration Details:

This training can also be customized to suit the needs of your institution upon request. You can have it delivered in our IRES Training Centre or at a convenient location. For further inquiries, please contact us on Phone: +254 715 077 817 or Email: [email protected].
The instructor led trainings are delivered using a blended learning approach and comprise of presentations, guided sessions of practical exercise, web-based tutorials and group work. Our facilitators are seasoned industry experts with years of experience, working as professional and trainers in these fields. All facilitation and course materials will be offered in English. The participants should be reasonably proficient in English.
Upon successful completion of this training, participants will be issued with an Indepth Research Institute (IRES) certificate certified by the National Industrial Training Authority (NITA).
Payment should be transferred to IRES account through bank on or before start of the course. Send proof of payment to [email protected].
Accommodation and airport pickup are arranged upon request. For reservations contact the Training Officer. Email: [email protected] Phone: +254 715 077 817.

Who else has taken this course?


# Job Title Organisation Country
1 Researcher IITA Kenya
2 Statistics Officer AFA Kenya
3 Researcher IITA Kenya