Data Science with R Certification Course

BY
Simplilearn

Become a Data Analytics wizard and learn statistical computing, graphics, data analysis, predictive analytics, and data visualisation with R.

Mode

Online

Fees

₹ 28320

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video and Text Based
Frequency of Classes Weekends

Course overview

The Data Science with R course has been thoroughly structured to imbue the candidates with a comprehensive knowledge of the different Analytics techniques that can be employed using R. The course offers case studies and projects to provide candidates with the necessary theoretical and practical exposure. On Data Science with R Certification Course by Simplilearn completion, the candidates will be well-versed in concepts like exploratory data analysis, descriptive and predictive analytics, and data visualisation with R.

With a Data Science with R certification course offering real-life industry-based projects, candidates will have ample hands-on experience during the learning process. Candidates will also get a fair idea of how data is utilized in the various sectors of the industry, as the projects cover a broad domain ranging from healthcare to finance. 

Moreover, candidates will gain mastery in the diverse statistical concepts like linear and logistic regression, cluster analysis, forecasting, hypothesis testing, and many other concepts pertaining to descriptive and inferential statistics.

The highlights

  • 10 real-life industry projects
  • Lifetime access to self-paced learning
  • Dedicated mentoring session by industry professionals
  • 64 hours of Blended learning

Program offerings

  • Blended learning
  • Corporate training
  • Self-paced learning
  • Lab and industry projects
  • Dedicated monitoring sessions

Course and certificate fees

Fees information
₹ 28,320

The fees for Data Science with R Certification is -

HeadAmount
Self Placed LearningRs. 28,320
Corporate TrainingNA
certificate availability

Yes

certificate providing authority

Simplilearn

Who it is for

The flexible course structure of Data Science with R Certification Course by Simplilearn encourages learning for candidates at all levels of experience who are interested in learning about Data Science with the R programming language. Some common profiles include –

  • IT Professionals
  • Analytics Professionals
  • Business Analysts
  • Software Developers
  • Students Pursuing Graduation/Post-Graduation

What you will learn

R programming Knowledge of data visualization Business analytics knowledge Data science knowledge Knowledge of programming algorithms
  • Have a detailed understanding of the various types and applications of Business Analytics, along with a brief overview of Business decisions and Data Science
  • Learn about the installation process of R, R-studio
  •  Learn how to set up a workspace suited to R and know more about various R packages. 
  • Gain competency in importing and exporting data in R
  • Identify, assign value, and manipulate data structures
  • Utilise the various graphic tools at your disposal to create beautiful charts and graphs
  • Learn about Hypothesis testing, Data sampling, and parametric test about population mean and variance
  • Learn and apply algorithms and methods like K-Means Clustering, DBscan clustering, Hierarchical clustering, and Apriori Algorithm

The syllabus

Lesson 00: Course Introduction

  • Course Introduction
  • Accessing Practice Lab

Lesson 01: Introduction to Business Analytics

  • Overview
  • Applications of Business Analytics
  • Data Science Overview
  • Business Decisions and Analytics
  • Types of Business Analytics
  • Knowledge Check
  • Conclusion

Lesson 02: Introduction to R Programming

  • Overview
  • Loops in R
  • Importance of R
  • Data Types and Variables in R
  • Operators in R
  •  Conditional Statements in R
  • Functions in R
  • R script
  • Conclusion
  • Knowledge Check

Lesson 03: Data Structures

  • Overview
  • Data Manipulation
  • Identifying Data Structures
  • Assigning Values to Data Structures
  • Demo Identifying Data Structures
  • Knowledge Check
  • Demo Assigning values and applying functions
  • Conclusion
  • Knowledge Check

Lesson 04: Data Visualization

  • Overview
  • Introduction to Data Visualization
  • ggplot2
  • File Formats of Graphic Outputs
  • Knowledge Check
  • Data Visualization using Graphics in R
  • Conclusion

Lesson 05: Statistics for Data Science-I

  • Overview
  • Data Sampling
  • Introduction to Hypothesis
  • Types of Hypothesis
  • Confidence and Significance Levels
  • Conclusion
  • Knowledge Check

Lesson 06: Statistics for Data Science-II

  • Overview
  • Hypothesis Tests about Population Means
  • Hypothesis Test
  • Parametric Test
  • Non-Parametric Test
  • Hypothesis Tests about Population Proportions
  • Hypothesis Tests about Population Variance
  • Conclusion
  • Knowledge Check

Lesson 07: Regression Analysis

  • Overview
  • Introduction to Regression Analysis
  • Non-Linear Regression
  • Types of Regression Analysis Models
  • Linear Regression
  • Demo Simple Linear Regression
  • Cross Validation
  • Non-Linear to Linear Models
  • Demo Regression Analysis with Multiple Variables
  • Principal Component Analysis
  • Factor Analysis
  • Conclusion
  • Knowledge Check

Lesson 08: Classification

  • Overview
  • Classification and Its Types
  • Demo Support Vector Machines
  • K-Nearest Neighbours
  • Logistic Regression
  • Support Vector Machines
  • Decision Tree Classification
  • Demo Decision Tree Classification
  • Random Forest Classification
  • Evaluating Classifier Models
  • Naive Bayes Classifier
  • Demo Naive Bayes Classifier
  • Demo K-Fold Cross Validation
  • Conclusion
  • Knowledge Check

Lesson 09: Clustering

  • Overview
  • Introduction to Clustering
  • Demo Hierarchical Clustering
  • Clustering Methods
  • Demo K-means Clustering
  • Conclusion
  • Knowledge Check

Lesson 10: Association

  • Overview
  • Demo Apriori Algorithm
  • Association Rule
  • Apriori Algorithm
  • Conclusion
  • Knowledge Check

Admission details


Filling the form

Step 1 - Visit the website- https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training

Step 2 - Click on Enroll now. You will be  redirected to a new page

Step 3 - If applicants have a coupon then they can simply apply or click on the Proceed. 

Step 4 -  Fill the required details likes name, email, and contact number, and click on proceed

Step 5 - Pay the Data Science with R Certification Course by Simplilearn fee and save the receipt of the transaction for future reference. 

How it helps

Learning Data Science with R course by Simplilearn can significantly increase your chances of landing a job since it is a sought-after and industry-revered skill to possess. Also, the analytics industry is on an unstoppable rise, with the industry to be valued at 40.6 Billion dollars by 2023. Having R as a skill can provide a necessary edge to your profile, setting you apart from your competitors. 

What’s more, the salary hikes in the analytics industry are on an average, 50% higher than anywhere in the IT industry. The Data Science with R certification course also offers industry-level projects, which will reflect your competency with the R platform and provide a competitive edge.

FAQs

How many times can I appear for the exam to pass the Data Science certification exam?

Candidates will have a maximum of three attempts to clear the Data Science with R Certification Course by Simplilearn exam.

How long is Data Science with an R Certificate valid for?

 The certificate has lifelong validity.

If I could not pass the Data Science certification exam, how soon can I retake it?

Candidates can re-attempt the Data Science with R Certification Course by Simplilearn exam immediately on failing.

If I qualify in the Data Science certification exam, when and how do I receive my certificate?

Upon passing, the students will receive a certificate for the Data Science certification course through the learning management system (LMS), which they can download and share.

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