R Programming Ninja Course 2025:Data Science with 5 Projects

Complete Beginner to Expert Guide with detailed theory, challenges,Case Studies and Projects .Many courses in one!!

What you'll learn
- R Programming
- R Datatypes
- R Data Structures
- Vectors, Matrices, Arrays, Lists
- Data analysis
- Data Visualization using GGPLOT2
- Case Studies on Data analysis using R
- Projects on Data analysis using R
- Data Cleaning
- Data Transformations using tidyr, Dplyr
- String Manipulations using Stringr
- Handling Date and Time using Lubridate
- Projects on Data Visualization using R

Requirements
- None

Description
Data Science and Analytics is a highly rewarding career that allows you to solve some of the world’s most interesting problems. The field of data science has exploded in the past two decades and shows no signs of stopping any time soon. Many big or small businesses and companies wish to make use of the insights gained through the big data.

Due to its open-source nature and its extreme versatility, R has become the primary tool for statistical analysis and data science. With the industry facing a shortage of data scientists all over the world, both novice and professional R programmers can enter. R community represents the cutting-edge in the field of data science.

This course is made to give you all the required knowledge at the beginning of your journey, so that you don’t have to go back and look at the topics again at any other place. This course is the ultimate destination with all the knowledge, tips and trick you would require to start your career.

This course providesFull-fledged knowledge ofR, we cover it all.

Our exotic journey will include the concepts of:

What’s and Why’s of R programming Language –Understanding the need for Statistics, difference between Population and Samples, variousSampling Techniques.

Core knowledge forDataTypes.

StringManipulation and handling using Stringr Package

Data Structures(Vectors, Matrices, Arrays, List)

Loops and ConditionsandFunctionsfor programming skills in R.

Dataframesexplained in detail and perspective forData Analysis Process and Concepts.

Most importantlyData Transformationshave been covered to make you comfortable with how data should be handled and transformed for analysis.

Date Time Modulehelps to understand and handle date and time in R.

Descriptive Statisticsallows to explore the data summaries for statistics.

Data Visualization using GGPLOT2used for simple and complex visual analysis.

All the modules includepractice questionsandcase studiesto give you idea on the real world problems and enhancing problem solving skills.

5 Projectsallow you to perform analysis on datasets with scope for further exploring and enhancing skills while building confidence.

Who this course is for:
- Beginner
- Intermediate
- Advanced
More Info