Overview of Course

Data Science With R Training is a comprehensive online course designed to provide learners with a solid foundation in data science using the R programming language. This course covers everything from data manipulation and visualization to machine learning and statistical analysis, making it a must-have for anyone looking to start a career in data science.

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Course Highlights

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Comprehensive coverage of R programming and data science

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Practical exercises and real-world case studies

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Industry-relevant curriculum

Key Differentiators

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    Personalized Learning with Custom Curriculum

    Training curriculum to meet the unique needs of each individual

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    Trusted by over 100+ Fortune 500 Companies

    We help organizations deliver right outcomes by training talent

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    Flexible Schedule & Delivery

    Choose between virtual/offline with Weekend options

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    World Class Learning Infrastructure

    Our learning platform provides leading virtual training labs & instances

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    Enterprise Grade Data Protection

    Security & privacy are an integral part of our training ethos

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    Real-world Projects

    We work with experts to curate real business scenarios as training projects

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Skills You’ll Learn


R programming


Data manipulation and visualization


Exploratory data analysis


Statistical inference


Machine learning


Predictive modeling

Training Options

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1-on-1 Training

On Request
  • Option Item Access to live online classes
  • Option Item Flexible schedule including weekends
  • Option Item Hands-on exercises with virtual labs
  • Option Item Session recordings and learning courseware included
  • Option Item 24X7 learner support and assistance
  • Option Item Book a free demo before you commit!
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Corporate Training

On Request
  • Option Item Everything in 1-on-1 Training plus
  • Option Item Custom Curriculum
  • Option Item Extended access to virtual labs
  • Option Item Detailed reporting of every candidate
  • Option Item Projects and assessments
  • Option Item Consulting Support
  • Option Item Training aligned to business outcomes
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  • Improve employee morale, job satisfaction, and retention rates.
  • Reduce employee turnovers and associated costs, such as recruitment and onboarding expenses.
  • Obtain long-term organizational growth and success.

Course Reviews


  • Data Types
  • Introduction to Data Science Tools
  • Statistics
  • Approach to Business Problems
  • An overview of Analytics
  • Models and Algorithms
  • Importance of Data Science
  • Data Science as a Strategic Asset
  • R, Python, WEKA, RapidMiner

  • Overview of R
  • Introduction to R
  • Data Structures and Manipulation in R
  • Installing R on Vsrious Operating Systems
  • IDEs for R
  • Steps in R Initiation
  • Installing an R Package
  • Overview of Business Analytics
  • Introduction to Business Analytics
  • Analytics Technology and Resources
  • Need of Business Analytics
  • Types and Features of Business Analytics
  • Descriptive and Predictive Analytics
  • Business Decisions
  • Analytical Tools
  • Data Science as a Strategic Asset

  • Introduction
  • Types of Graphics
  • Save Graphics to a File
  • Graphics in R
  • Create a word cloud
  • Exporting Graphs in EStudio

  • Need of Hypothesis Testing in Businesses
  • Chances of Errors in Sampling
  • Level of Significance
  • Types of Statistical Hypothesis Tests
  • Test Statistic
  • Types of Errors
  • Use Normal and Student Probability Distribution Functions
  • Objectives of Null Hypothesis Test
  • Use Chi-Squared Test Statistics

  • Introduction to Regression Analysis and Usage
  • Types of Regression Analysis
  • Interaction Regression Model
  • Correlation
  • Logit Function
  • Lift charts
  • Decile Analysis

  • Introduction to Cluster Techniques
  • Examples of Classification
  • Classification Process - Model Construction
  • Data Preparation Issues
  • Basic Algorithm for a Decision Tree
  • Decision Trees in Data Mining
  • Naive Bayes Classifier
  • Clustering Models
  • Use Cases of Clustering
  • DBSCAN Clustering Algorithm
  • Distance Methodologies
  • Hierarchical and Non-Hierarchical Procedure
  • K-Means clustering
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  • RedtickMake informed decisions about whether to enroll in the course or not.
  • RedtickGet a perspective with a glimpse of what the learning process entails.
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Inquiry for :


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Target Audience:

  • Data analysts
  • Business analysts
  • IT professionals
  • Graduates seeking a career in data science
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  • Basic knowledge of statistics
  • Basic programming skills
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Benefits of the course:

  • Gain proficiency in R programming and data science
  • Enhance your career prospects with in-demand skills
  • Learn from industry experts
  • Practical, hands-on learning experience
  • Access to a community of learners and industry experts
  • 24/7 online support
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Exam details to pass the course:

  • The course is self-paced and does not have a final exam.
  • Learners will receive a certificate of completion upon finishing the course.
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Certification path:

  • Certified Data Scientist with R Programming by Data Science Council of America
  • IBM Data Science Professional Certificate
  • Microsoft Certified: Azure Data Scientist Associate
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Career options after doing the course:

  • Data scientist
  • Data analyst
  • Business analyst
  • Machine learning engineer
  • Data engineer

Why should you take this course from Skillzcafe:

Why should you take this course from Skillzcafe:
  • Bullet Icon Industry-relevant curriculum
  • Bullet Icon Taught by industry experts
  • Bullet Icon Practical, hands-on learning experience
  • Bullet Icon Access to a community of learners and industry experts
  • Bullet Icon 24/7 online support
  • Bullet Icon Affordable pricing


Yes, this course is suitable for beginners with basic programming and statistics knowledge.

The course duration is 50 hours.

Yes, learners will receive a certificate of completion after finishing the course.

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