Course Overview
R is a high-level statistical language and is widely used among statisticians and data miners to develop statistical applications. This solution-based video will be your guide, taking you through different programming aspects with R.
Beginning with the basics of R programming, this course provides step-by-step resources and time-saving methods to help you solve programming problems efficiently. Starting with the installation of R, each recipe addresses a specific problem with a discussion that explains the solution and offers insight into how it works.
You will learn to work with powerful R tools and techniques. You'll be able to boost your productivity with the most popular R packages and tackle data structures such as matrices, lists, and factors. You'll see how to create vectors, handle variables, and perform other core functions. You'll be able to tackle issues with data input/output and will learn to work with strings and dates.
Details of the course is mentioned below :
Course Modules
You will learn :
- How to run R code
- Introduction to functions
- - Variable Scope
- - Default Arguments
- - Vectors, the R Workhorse
- - Character Strings
- - Matrices
- - Lists
- - Data Frames
- - Classes
- Scalars, Vectors, Arrays and Matrices
- - Adding and Deleting Vector Elements
- - Obtaining the Length of a Vector
- - Matrices and Array as Vectors
- Declarations
- Recycling
- Common Vector Operations
- - Vector Arithmetic and Logical Operator
- - Vector Indexing
- - Generating Useful Vectors with the : Operator
- - Generating Vector Sequences with seq()
- - Repeating Vector Constraints with rep()
- Using all() and any()
- Vector Operations
- NA and NULL() values
- Filtering data
- - Generating Filtering Indexes
- - Filtering with the subset() functions
- - The Selection Function which()
- A Vectorized if-then-else: the ifelse() statement
- Testing Vector Equality
- Vector Element Names
- More on c()
- Packages for R
- Tidyverse Library
- Piping commands with %>%
- Sample Dataset
- Importing data from Excel
- Data Visualization
- - Using colours in R
- - Creating Bar Charts
- - Creating Histograms
- - Creating box plots
- - Creating scatterplots
- - Creating line charts
- - Creating cluster charts
- Selecting cases and subgroups
- Recoding variables
- Computer new variables
- Data Analysis
- - Computing Frequencies
- - Computing Descriptive
- - Computing Correlations
- - Computing Linear Regression
- - Computing contingency tables
- Creating Tidy Tables
- Using tibbles
- Using data.table
- Converting data from wide to tall
- Converting data from tall to wide
- Converting data from tables to rows
- Working with dates and time
- Working with list data
- Working with XML data
- Working with JSON data
- Working with categorical variable
- Filtering cases and subgroups
- Recording categorical data
- Recording quantitative data
- Transforming outliers
- Creating scale score by counting
- Creating scale score by calculating averages
- Captstone Project
FAQ
Any graduate, fresher, experienced and looking to start or change their career into data analytics can attend. No prior experience is mandatory.
Absolutely. We start the training from scratch. After completing the course you will not feel that you have never programmed.
Yes
Our trainers are from the industry. Every class is followed by real time assignments which will make you feel confident when you get into a job.
Fully online. You can attend from anywhere. You just need a laptop and a good internet connection
Yes 100%. It is live and fully interactive. We dont believe in running through power point presentations.
Please contact on the given number.
Contact Us
+91 70198 30464 / +91 79911 97543
Enroll / Enquire
Address : Saroj Iris, No. 106 (Wing A), Gunjur, Varthur Hobli, Bangalore - 560087
Phone : +91 70198 30464 / +91 79911 97543
Email :
info@dakshahanalyticsacademy.com, dakshahanalyticsacademy@gmail.com