Data Science with R Programming

Are you planning to make your career in data science? Then this Hatigen's Data Science with R Programming Certification Course is for you. Become an expert in data analytics with our dedicated mentoring sessions, hands-on experience with real-time projects, and all-time support from our faculty team. This Data Science with R Programming Course enables you to analyze data and make better business decisions. Therefore, with our well-structured cutting-edge curriculum, upskill your knowledge in data science with R.

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Data Science with R Course Overview

In Data Science with R Certification Training Program, you will be dedicated to learning data visualization, data exploration, and descriptive as well as predictive analytics with R language. Adding to this, our expert team of faculty and mentors will train you to import and export data in R, statistical concepts, data structures in R, etc.

Data Science with R Online Training – Key Features

  • Trusted content
  • Re-learn for free anytime in a year
  • Rigorous assignments and assessments
  • Learn at your own pace
  • Mandatory feedback sessions
  • Mock-interviews
  • Hands-on real-time experience
  • Free mentorship
  • Live chat for instant solutions
  • Job-ready employees post-training
  • End-to-end training
  • Download the certificate after the course
Data Science with R – Skills Covered: Business analytics. R programming and its packages. Data structures and data visualization. Apply functions and DPLYR function. Graphics in R for data visualization. Hypothesis testing. Apriori algorithm. Kmeans and DBSCAN clustering.

Data Science with R Programming Course – Benefits

The Data Science platform is expected to expand its market size from 2021 to 2026. Therefore, people who are interested to enter into the data science field can learn R programming and join this data science with R programming to explore wider career opportunities.

Designation
Annual Salary
Hiring Companies
Job Wise Benefits
Designation
Data Scientist

UK
Hiring Companies
Designation
Data Analyst

UK
Hiring Companies

Data Science with R Online Course – Training Options

Self-Paced Learning

£ 1200

  • 1-year access to the Blockchain course content
  • 1 capstone project
  • Multiple assessments
  • Continuous feedback sessions
  • Access to the class recordings
  • Assistance and support
  • Download certification
  • Free mentorship

Online Boot Camp

£ 1000

  • Everything in Self-paced learning +
  • On-spot doubt clarification
  • Interactive training sessions
  • Sessions on the capstone project
  • Live, online classroom training
  • Mock-interviews

Corporate Training

Customized to your team's needs

  • 1-year access to the Blockchain course content
  • 1 capstone project
  • Multiple assessments
  • Continuous feedback sessions
  • Class recordings
  • Assistance and support
  • Certification after the course

Data Science with R Online Certification Course – Curriculum

Eligibility

Candidates who want to make their career in data science or IT professionals, and software developers planning to switch to Data Science roles can join this Data Science with R Certification Course.

Pre-requisites

Before you begin this Data Science with R certification course, you can get some basic knowledge of R. However, even a beginner with no R knowledge can join this course as our expert faculty at Hatigen trains you from the scratch.

Course Content

  • Course Introduction
  • Accessing Practice Lab
  • Lesson 01 - Introduction to Business Analytics
  • 1.001 Overview
  • 1.002 Business Decisions and Analytics
  • 1.003 Types of Business Analytics
  • 1.004 Applications of Business Analytics
  • 1.005 Data Science Overview
  • 1.006 Conclusion
  • Knowledge Check
  • 2.001 Overview
  • 2.002 Importance of R
  • 2.003 Data Types and Variables in R
  • 2.004 Operators in R
  • 2.005 Conditional Statements in R
  • 2.006 Loops in R
  • 2.007 R script
  • 2.008 Functions in R
  • 2.009 Conclusion
  • Knowledge Check
  • 3.001 Overview
  • 3.002 Identifying Data Structures
  • 3.003 Demo Identifying Data Structures
  • 3.004 Assigning Values to Data Structures
  • 3.005 Data Manipulation
  • 3.006 Demo Assigning values and applying functions
  • 3.007 Conclusion
  • Knowledge Check
  • 4.001 Overview
  • 4.002 Introduction to Data Visualization
  • 4.003 Data Visualization using Graphics in R
  • 4.004 ggplot2
  • 4.005 File Formats of Graphic Outputs
  • 4.006 Conclusion
  • Knowledge Check
  • 5.001 Overview
  • 5.002 Introduction to Hypothesis
  • 5.003 Types of Hypothesis
  • 5.004 Data Sampling
  • 5.005 Confidence and Significance Levels
  • 5.006 Conclusion
  • Knowledge Check
  • 6.001 Overview
  • 6.002 Hypothesis Test
  • 6.003 Parametric Test
  • 6.004 Non-Parametric Test
  • 6.005 Hypothesis Tests about Population Means
  • 6.006 Hypothesis Tests about Population Variance
  • 6.007 Hypothesis Tests about Population Proportions
  • 6.008 Conclusion
  • Knowledge Check
  • 7.001 Overview
  • 7.002 Introduction to Regression Analysis
  • 7.003 Types of Regression Analysis Models
  • 7.004 Linear Regression
  • 7.005 Demo Simple Linear Regression
  • 7.006 Non-Linear Regression
  • 7.007 Demo Regression Analysis with Multiple Variables
  • 7.008 Cross Validation
  • 7.009 Non-Linear to Linear Models
  • 7.010 Principal Component Analysis
  • 7.011 Factor Analysis
  • 7.012 Conclusion
  • Knowledge Check
  • 8.001 Overview
  • 8.002 Classification and Its Types
  • 8.003 Logistic Regression
  • 8.004 Support Vector Machines
  • 8.005 Demo Support Vector Machines
  • 8.006 K-Nearest Neighbours
  • 8.007 Naive Bayes Classifier
  • 8.008 Demo Naive Bayes Classifier
  • 8.009 Decision Tree Classification
  • 8.010 Demo Decision Tree Classification
  • 8.011 Random Forest Classification
  • 8.012 Evaluating Classifier Models
  • 8.013 Demo K-Fold Cross Validation
  • 8.014 Conclusion
  • Knowledge Check
  • 9.001 Overview
  • 9.002 Introduction to Clustering
  • 9.003 Clustering Methods
  • 9.004 Demo K-means Clustering
  • 9.005 Demo Hierarchical Clustering
  • 9.006 Conclusion
  • Knowledge Check
  • 10.001 Overview
  • 10.002 Association Rule
  • 10.003 Apriori Algorithm
  • 10.004 Demo Apriori Algorithm
  • 10.005 Conclusion
  • Knowledge Check

Data Science with R Training Course – FAQs

Data Science is one of the highly demanded technologies in the corporate industry offering an amazing career path for professionals who are aiming for high-earning potential jobs. This career domain majorly comprises statistics that is mostly used for data analysis and R is considered the bridging language of this domain. Furthermore, before you get into this data science with the R training course, you can learn the basics of R programming through tutorial sessions so that you can get a clearer idea of the concepts during this course.

Python and R programming are renowned to be the high-end languages with their own pros and cons. However, if you are willing to start your career in Data Science, you can make your own choice of choosing python or R based on the projects and their scope in the long run. Furthermore, you can also learn Data Science with Python Course at Hatigen from our expert trainers and boost your skills that are essential to becoming a data scientist.

Yes, the course material provided by Hatigen for the Data Science with R programming course is highly effective and helps you to grasp all the essential concepts easily. Therefore, with a clear understanding of the concepts, you can deliver the best in the certification exam and become job-ready for a data scientist role.

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