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Data Science With R Online Training

This course deals with online training of Data Science With R. This program will provide you with various concepts of R programming for data science. This program R for Data science is crafted by our leading instructors in R programming. We also provide certification training that will make you ready for real-time scenarios.

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Course Overview

R for Data Science is one of the most widely used languages for statistical computing and data analysis. Data science using R programming language focuses on the languages’ graphical and statistical use. In this R for a data science course, you will learn how to perform data visualization and statistical analysis. The R program language is open-source software.

Key Features.

  • Introduction to basics of R programming language.
  • Install and configuration of R 
  • Insights into simulations for data science with R
  • Concepts of Data Science with R workflow 
  • Learn and practice R for data science solutions.
  • Guidance for Data science for R certification. 
  • Guidance in resume building for R programming.
Who should take this course?

This course benefits professionals who are already into programming and want to change in the R environment. Individuals with knowledge of statistics can also pursue a career in R programming. Beginners in R programming can practice with this course. Individuals who are interested in getting data science with R certification can also do this course.

Course curriculum
    • Overview
    •  Business Decisions and Analytics
    •  Types of Business Analytics
    • Applications of Business Analytics
    • Data Science Overview
    • Conclusion
    • Knowledge Check
    • Overview
    •  Importance of R
    • Data Types and Variables in R
    • Operators in R
    • Conditional Statements in R
    •  Loops in R
    • R script
    • Functions in R
    • Conclusion
    • Knowledge Check
    • Overview
    •  Identifying Data Structures
    • Demo: Identifying Data Structures
    • Assigning Values to Data Structures
    •  Data Manipulation
    •  Demo: Assigning Values and Applying Functions
    •  Conclusion
    •  Knowledge Check
    • Overview
    • Introduction to Data Visualization
    •  Data Visualization Using Graphics in R
    •  Ggplot2
    • File Formats of Graphic Outputs R
    •  Conclusion
    • Knowledge Check
    • Overview
    • Introduction to Hypothesis
    • Types of Hypothesis
    •  Data Sampling
    •  Confidence and Significance Levels
    • Conclusion
    •  Knowledge Check
    • Overview
    • Hypothesis Test
    •  Parametric Test
    • Non-Parametric Test
    • Hypothesis Tests about Population Means
    •  Hypothesis Tests about Population Variance
    • Hypothesis Tests about Population Proportions
    •  Conclusion
    • Knowledge Check
    • Overview
    • Introduction to Regression
    •  Analysis Types of Regression
    • Analysis Models Linear Regression
    • Demo: Simple Linear Regression
    • Non-Linear Regression
    • Demo: Regression Analysis with Multiple Variables
    • Cross Validation
    • Non-Linear to Linear Models
    • Principal Component Analysis
    •  Factor Analysis
    • Conclusion
    • Knowledge Check
    • Overview
    •  Classification and Its Types
    • Logistic Regression
    • Support Vector Machines
    • Demo: Support Vector Machines
    •  K-Nearest Neighbours
    • Naive Bayes Classifier
    • Demo: Naive Bayes Classifier
    • Decision Tree Classification
    •  Demo: Decision Tree Classification
    • Random Forest Classification
    • Evaluating Classifier Models
    •  Demo: K-Fold Cross Validation
    • Conclusion
    •  Knowledge Check
    • Overview
    •  Introduction to Clustering
    • Clustering Methods
    • Demo: K-means Clustering
    •  Demo: Hierarchical Clustering
    • Conclusion
    • Knowledge Check
    • Overview
    • Association Rule
    • Apriori Algorithm
    • Demo: Apriori Algorithm
    • Conclusion
    • Knowledge Check
Data Science With R Online Training FAQ’s:
1.Which is better for data science R or Python?

Both have different purposes and both are useful.
Python is a general programming language used more in machine learning workflows.
R is used for graphical and statistical computing .

2.How do I get R certification?

You have to write the proctored exam for R certification in the Prometric center. This Data Science with R course will help you to take and pass the exam confidently.

3.Do we provide data science with r certification?

Yes, we provide the certification on completion of the course. This certification will make you stand out in the programming market and get hired easily.

4.Is R easy to learn?

If you are having a statistical background in mathematics and have a flair for learning programming then it's an easy job.

5.Are The Data Science With R Jobs Pay High?

Yes, data science with R jobs is among the highest paid in the US. The job market for such professionals is growing.

6.Do You Provide R For The Data Science Exercise?

Yes, we provide R for data science exercises and solutions.

7.What are the different Job roles in R language?

The different Job roles in R language are.
R programmer
R developer
Data analyst
Data scientist.

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