R Programming | Free Certification Course

 Free premium Certificate Course:R Programming | Free Certification Course


1. Fundamentals of R Language 

Introduction to R 

History of R 

Why R programming Language 

Relationship among R and Python 

Utilization of R 

2. Course of action of R Language 

Close by Environment course of action 

Presenting R on Windows 

Presenting R on Linux 


What is RStudio? 

Foundation of RStudio 

First Program - Hello World 

3. Variables and Data Types 

Elements in R 

Attestation of variable 

Variable undertaking 

Finding variable 

Data types in R 

Data type change 

R programs for Variables and Data types in RStudio 

4. Data Output Features in R 

channel() work 

readline() work 

stick() work 

paste0() work 

cat() work 

R Programs for executing these limits in RStudio 

5. Overseers in R 

Number shuffling Operators 

Social Operators 

Reasonable Operators 

Undertaking Operators 

Different Operators 

R Programs to perform various assignments using overseers in RStudio 

6. Data Structure in R (part-I) 

What is data structure? 

Kinds of data structure 


- What is a vector in R? 

- Creating a vector 

- Accessing part of vector 

- Some more technique on vectors 

- R Programs for vectors in RStudio 

Utilization of Vector in R 


- What is a summary in R? 

- Creating a once-over 

- Accessing part of overview 

- Modifying part of overview 

- Some more technique on list 

R Programs for list in RStudio 

7. Data Structure in R (part-II) 

Grid or Matrices 

- What is grid in R? 

- Creating a grid 

- Accessing part of cross section 

- Modifying part of cross section 

- Matrix Operations 

R Programs for grids in RStudio 

Use of Matrices in R 


- What are groups in R? 

- Creating a group 

- Naming lines and areas 

- Accessing part of a bunch 

- Some more technique on bunches 

R Programs for groups in RStudio 

8. Data Structure in R (part-III) 

Data diagram 

- What is a data diagram in R? 

- Creating a data diagram 

- Accessing part of data plot 

- Modifying part of data plot 

- Add the new part or fragment in data layout 

- Deleting part of data plot 

- Some more technique on data plot 

R Programs for data diagram in RStudio 


- Factors in R 

- Creating a factor 

- Accessing segment of factor 

- Modifying segment of factor 

R Programs for Factors in RStudio 

Utilization of Factors in R 

9. Dynamic in R 

Preamble to Decision making 

Kinds of dynamic decrees 

Introduction, etymological structure, flowchart and tasks for 

- if clarification 

- if… else clarification 

- if… else if… else clarification 

- switch clarification 

10. Hover control in R 

Preamble to hovers in R 

Sorts of circles in R 

- for circle 

- while circle 

- reiterate circle 

- settled circle 

break and next verbalization in R 

Introduction, sentence structure, flowchart and tasks for 

- for circle 

- while circle 

- repeat circle 

- settled circle 

11. Limits in R 

Preface to work in R 

Worked in Function 

Customer described Function 

Making a Function 

Limit Components 

Calling a Function 

Recursive Function 

Various tasks for limits in RStudio 

12. Strings in R 

Preamble to string in R 

- Rules to create R Strings 

- Concatenate at any rate two strings in R 

- Find length of String in R 

- Extract Substring from a String in R 

- Changing the case for instance Upper to cut down case and lower to promoted 

Various ventures for String in RStudio 

13. Packs in R 

Preamble to Packages in R 

Get the summary of the significant number of groups presented in RStudio 

Foundation of the packs 

The best strategy to use the packs in R 

Accommodating R Packages for Data Science 

R program for pack in RStudio 

14. Data and File Management in R 

Getting and Setting the Working Directory 

Commitment as CSV File 

Exploring the CSV File 

Creating into a CSV File 

R undertakings to execute CSV record 

15. Plotting in R (Part-I) 

Line outline 


Pie Charts 

3D Pie Chart 

16. Plotting in R (Part-II) 

Bar/line outline 


Box plot 

Who this course is for: 

R Developers and Data Developers 

Data Scientists - R, Python 

Beginners and students longing for an occupation in programming and quantifiable examination 

Data Engineers and Statistical Analysts 

R and Python Programmers 

Particular and Analytics Consultants 

Anyone wishing to learn data science and AI 

Lead R Developers 

R Modeling Analysts 

Data Software Developers 

Budgetary and Marketing Analysts 

Programming Engineers 

Web Application Developers 

Business Analysts and Consultants 

Data Science and Machine Learning fans

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