Registrations accepted up to December 2nd, 2021

R Programming A-Z™: R For Data Science With Real Exercises!

Learn Programming In R And R Studio. Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2

Syllabus:

Chapter - I: Install R & R Studio; Basics of R: Introduction, R-Calculator, Data Types, Variables, Vectors, Tables, Lists, Factors, Matrix and Data Frames.

Chapter - II: Operators: Arithmetic operators, Relational operators, Logical operators, Assignment operators and Miscellaneous operators; Conditional Statements: If Statement, if else Statement, ifelse Statement and switch Statement.

Chapter - III: Looping Statements: For loop, while loop, repeat and Conditional Looping (break & next).

Chapter - IV: User Defining Functions and Inbuilt functions.

Chapter - V & VI: Import Datasets: read.csv( ), read.table( ); Packages: install packages, load packages, dplyr package: select, filter, arrange, rename, mutate, summarize, group_by, contains, starts_with, ends_with, Joins(left_join, right_join, inner_join, full_join, anti_join, semi_join), apply, sapply and lapply.

Chapter - VII: Visualization: scatter plot, bar plot, box plot, Histogram, pie chart, line chart and ggplot2.

Chapter - VIII: Statistical analysis: Descriptive statistics: mean, median, mode, minimum, maximum, range, variance, standard deviation, Skewness, kurtosis, etc. Inferential statistics: t-test, F - test, Z – test, Chi-square test and ANOVA; Regression Analysis: linear, multiple and logistic regression; Forecasting techniques: ARIMA models and assignment – VIII.

Chapter - IX: Machine Learning Algorithms

Note: If you want R Programming Syllabus download here.

Requirements

No prior knowledge or experience needed. Only a passion to be successful!

Description

Learn R Programming by doing!

There are lots of R courses and lectures out there. However, R has a very steep learning curve and students often get overwhelmed. This course is different!

This course is truly step-by-step. In every new tutorial, we build on what had already been learned and move one extra step forward.

After every class, you learn a new valuable concept that you can apply right away. And the best part is that you learn through live examples.

This training is packed with real-life analytical challenges which you will learn to solve. Some of these we will solve together, some you will have as homework exercises.

In summary, this course has been designed for all skill levels and even if you have no programming or statistical background you will be successful in this course!

I can't wait to see you in class,

Sincerely,

Saraswathi Analytics.