Learning Path: Data Science with R

Introduction to R Programming 49 lectures 03:46:41 Introduction to R Programming - The Course Overview This video provides an overview of the entire course. Installing R The aim of this video is to show how to install R on our system.

• Visit the CRAN website
• Choose the download option based on your operating system
• Follow the standard procedure for installing R

Installing RStudio To run and write code in R, we first need to focus on how to get and install the IDE.

• Go to RStudio.com
• Download the correct version of the software
• Install the latest version

Installing Packages We have installed R and RStudio. Now let’s check out how to install the packages.

• Explain what a package contains
• Check out the sources of packages
• Learn how to install them

Data Types and Data Structures The aim of this video is to teach you what data types and data structures in R are.

• Explain data types
• Explain data structures
• Show some examples in R

Vectors In this video, we will see how to work with vectors in R.

• Explain how to create a vector
• Create different types of vectors
• Access specific items within a vector

Random Numbers, Rounding, and Binning The aim of this video is to show how to work with random numbers and do rounding and binning.

• Show how to create random numbers
• How to round
• How to bin numeric vectors

Missing Values Taking vectors a step ahead, let’s see how we can to handle missing values.

• Explain how to find missing values
• Explain how to omit the missing values

The which() Operator We now know a lot about how vectors work, but how do we get specific items from a vector based on any condition? Let’s check out just that in this video.

• How to write conditions
• How to write complex conditions
• How to use the which() operator to get the required items

Lists This video will introduce a new data structure called list and how to work with it.

• Understand what lists are
• See when lists are used
• Learn how to perform data manipulation with lists

Set Operations In this video, our goal is to understand how to perform set operations in R.

• Explain the syntax of important set operations such as union, intersect and so on
• Perform the set operations to grasp the usage

Sampling and Sorting What is sampling and sorting and how to do it in R?

• Explain sampling
• Show how to do it in R
• Explain how to sort in R

Check Conditions Checking conditions is often a requirement for a programmer to write maintainable code. Let’s understand how we can check conditions in R.

• Show how to write if and else statements
• Grasp the correct usage of ifelse()

For Loops You may have come across several instances whilst coding where you need to perform repetitive operations through loops, right? In this video, we’ll see how to do that in R using for loops.

• Explain the for loop’s syntax
• Show how to skip an iteration
• Check out how to break out from a loop

Dataframes Let’s explore what data frames are and how to work with them.

• Learn how create a data frame
• Access elements in a data.frame: select, filter, and so on
• Understand the functions related to data frames

Importing and Exporting Data In this video, we will check out how to import and export data in R.

• Show the function used to import different forms of data
• Check out the functions used to export various forms of data

Matrices and Frequency Tables The aim of this video is to check out how to work with matrices and frequency tables.

• Learn how to create a matrix
• Access data in a matrix
• Grasp how to generate frequency tables

Merging Dataframes Our goal in this video is to use W to merge data frames.

• Learn different types of merges
• Understand how to use them in R

Aggregation How to do aggregation in R?

• Different variations of aggregation
• How to do it in R

Melting and Cross Tabulations with dcast() In this video, we will look at how to de-aggregate data frames and create cross tabulations.

• Show the melt function
• Show the dcast() function from the reshape2 package

Dates In this video, we will look at how to handle date variables in R.

• Introduce the lubridate package
• Understand the date format
• Learn the Date operations

String Manipulation The goal of this video is to see how to perform string operations in R.

• Introduce the paste function for concatenating
• Introduce the stringr package

Functions Let’s learn how to avoid code replication.

• Introduce functions
• Understand the best practices by writing functions in R

Debugging and Error Handling The aim of this video is to understand how to debug and handle errors.

• Learn the 3 ways used to debug in R
• Grasp the 2 ways to handle errors in R

Fast Loops with apply() We’ll see in this video how to write fast loops with apply().

• Introduce the syntax
• Explain the difficult part of using apply functions

Fast Loops with sapply(), lapply() and vapply() Sometimes we’d want to iterate through lists. What do we do then? Let’s learn using fast loops with sapply, vapply and lapply to help us achieve this goal.

• Explain sapply
• Explain lapply and how it is different

Creating and Customizing an R Plot How to make plots and customize them.

• Show how to use the plot function
• Make a scatterplot
• Explain the arguments and features of the plot function

Drawing Plots with 2 Y Axes Sometimes, just a single Y axis is not enough. It becomes difficult to depict the variations for two variables on different scales in the same chart. To solve this, we’ll look at how to make a plot with two Y axes.

• Show the method
• Show the syntax to make two Y axes

Multiplots and Custom Layouts In this video, we will learn how to make multiple plots and custom layout to get better at our analyzing skills.

• Show how to make multiple plots
• Show how to customize plot layouts

Creating Basic Graph Types The aim of this video is to create different types of plots.

• Show how to make a histogram, a bar chart, and a density plot
• Show how to make dot plots and box plots

Univariate Analysis What are the steps and actions one needs to do as part of data analysis before jumping to predictive modeling? Let’s understand this better.

• Explain the different steps
• Show how to do univariate analysis of numeric variables
• Show how to do univariate analysis of categorical variables

Normal Distribution, Central Limit Theorem, and Confidence Intervals The aim of this video is to teach you what normal distribution, central limit theorem, and confidence intervals are.

• Explain the concept behind normal distribution and CLT
• Show the R code implementation
• Explain confidence intervals and implement them in R

Correlation and Covariance In this video, we will understand correlation and Covariance, the concept behind them, and their implementation in R.

• Explain correlation and covariance
• The concept and the difference between them
• Implement them in R

Chi-sq Statistic What is the chi-square statistic, when is it used, and how to do the chi-sq test?

• Explain the chi-sq statistic and its purpose
• Explain the meaning behind it
• Show the R implementation

ANOVA What is ANOVA, its purpose, when to use it, and how to implement it in R?

• Explain the concept and purpose
• When to use it
• How to implement it in R

Statistical Tests What are the other commonly used statistical tests in R and how to implement them?

• Explain the one and two sample t-test, parametric versus non-parametric
• Explain the Wilcoxon signed rank test
• Show the R implementation

Project 1 – Data Munging and Summarizing All knowledge is incomplete without being put to practice. We’ve got a good taste of the core concepts that govern statistical analysis with R. Let’s solve the challenges pertaining to data manipulation in this video.

• Run through the basics of data handling
• Understand the Unique key
• Solve the proposed challenges

Project 2 – Visualization with Base Graphics What is data if not represented visually! We have solved challenges related to data manipulation. Now it’s time to tackle visualization in this video.

• Create a histogram on the given data
• Create a line chart with multiple lines
• Create a box plot

Project 3 – Statistical Inference Practice solving exercises that involve making statistical inferences.

• Test the statistical significance between two continuous variables
• Problem that tests statistical significance between continuous and categorical variable

Pipes with Magrittr The aim of this video is to introduce the magrittr package, its significance, and features such as pipe operators.

• Why use magrittr and pipes
• Explain various pipe operators in magrittr
• Show the R code implementation and suitable examples

The 7 Data Manipulation Verbs Understand and use the 7 data manipulation verbs.

• What are the 7 data manipulation verbs?
• Why are they simple and widely adopted?
• Implementation in R for all the verbs

Aggregation and Special Functions How to group datasets by one or more variables using dplyr.

• Explain the process of grouping
• Explain the group_by and summarize functions
• Show the implementation in R

Two Table Verbs How to join two tables using the two table verbs of dplyr.

• Explain the two table verbs
• Explain the different types of joins
• Show the implementation in R

Working With Databases How to work with databases with DplyR.

• Create a SQLite DB and upload data
• Pull partial data and do manipulation
• Download full data and see the SQL

Understanding Basics, Filter, and Select Understand the basics of data.table; do filter and select operations.

• Explain the purpose and significance of data.table
• How the syntax differs generally and how to filter and select
• Show the R code implementation

Understanding Syntax, Creating and Updating Columns Understand the syntax; create and update columns in a data.table.

• Understand the general syntax in sync with SQL syntax
• Create new columns
• Update the columns

Aggregating Data, .N, and .I Learn how to aggregate data.tables. Also learn the .N and .I operators.

• The syntax to group data
• The .N and .I operators – using them effectively
• The R code implementation

Chaining, Functions, and .SD Understand and implement chaining, keys, functions, and .SD.

• How to set keys and why
• Write apply family functions within data.table
• Show the usage of .SD

Fast Loops with set(), Keys, and Joins How to write for-loops with set, set keys, and join data.tables?

• Explain how to use set() and why it’s great
• How to set keys and filter data.tables
• Show how to do joins using square brackets and merge function

Introduction to R Programming. 49 lectures 03:46:41 Introduction to R Programming - The Course Overview This video provides an overview of the entire course. Installing R The aim of this video is to show how to install R on our system.

• Visit the CRAN website
• Choose the download option based on your operating system
• Follow the standard procedure for installing R

Installing RStudio To run and write code in R, we first need to focus on how to get and install the IDE.

• Go to RStudio.com
• Download the correct version of the software
• Install the latest version

Installing Packages We have installed R and RStudio. Now let’s check out how to install the packages.

• Explain what a package contains
• Check out the sources of packages
• Learn how to install them

Data Types and Data Structures The aim of this video is to teach you what data types and data structures in R are.

• Explain data types
• Explain data structures
• Show some examples in R

Vectors In this video, we will see how to work with vectors in R.

• Explain how to create a vector
• Create different types of vectors
• Access specific items within a vector

Random Numbers, Rounding, and Binning The aim of this video is to show how to work with random numbers and do rounding and binning his video is to show how to install R on our system.

• Visit the CRAN website
• Choose the download option based on your operating system
• Follow the standard procedure for installing...