R Programming Course for Data Science

Teaching Krow’s R Programming Course For Data Science makes you an expert in data analytics leveraging the R programming language. The certification training will enable you to efficiently polish your data science skills for various companies and help them analyze data and make effective and prompt business decisions. The course will also aid you in developing a better understanding of Time Series, Statistics, Text Mining, and introduction to Deep Learning. Teaching Krow’s R Programming Course for Data Science will help you clear the certification exam on your first attempt.

Why should you take R Programming Course for Data Science ?

Promotes faster development and processing.

Offers you to select the best company from the pool of opportunities available to you and attracts higher paying packages.

Earn a globally recognized certificate and learn from the experts.


40 hours of instructor-led training
16 hours of self-paced videos
Projects and exercises
One year access
Training completion certificate

R Programming Course for Data Science Overview

What Will You Learn In The R Programming Course for Data Science by Teaching Krow?
  • Basics of R programming language
  • Performing sorting and analyzing variance
  • Working with RStudio for data modelling
  • Reading ODBC Table & database connectivity
  • R functions like Merge, Stack, and strsplit
  • R integration with the Hadoop platform


Self Paced Training


R Programming Course for Data Science Curriculum

Introduction to Data Science With R
  • What is Data Science?
  • What does Data Science involve?
  • Business Intelligence vs Data Science
  • The era of Data Science
  • Lifecycle of Data Science
  • Tools of Data Science
  • Introduction to R
  • Introduction to Big Data and Hadoop
  • Introduction to Spark
  • Introduction to Machine Learning
  • What is Statistical Inference?
  • Terminologies of Statistics
  • Measures of Centers
  • Measures of Spread
  • Probability
  • Normal Distribution
  • Binary Distribution
  • Data Analysis Pipeline
  • What is Data Extraction?
  • Types of Data
  • Visualization of Data
  • Raw and Processed Data
  • Data Wrangling
  • Exploratory Data Analysis
  • What is Machine Learning?
  • Machine Learning Categories
  • Machine Learning Use-Cases
  • Machine Learning Process Flow
  • Supervised Learning algorithm
  • What are classification & d its use cases?
  • What is a Decision Tree?
  • Algorithm for Decision Tree Induction
  • Confusion Matrix
  • Building a Perfect Decision Tree
  • What is Random Forest?
  • What is Naive Bayes?
  • Support Vector Machine
  • What are Clustering and its use cases
  • What is K-means Clustering?
  • What is Canopy Clustering?
  • What is C-means Clustering?
  • What is Hierarchical Clustering?
  • What are Association Rules and their use cases?
  • What is the Recommendation Engine, and it’s working?
  • Types of Recommendations
  • User-Based Recommendation
  • Item-Based Recommendation
  • Difference Between User-Based and Item-Based Recommendations
  • Recommendation use cases
  • The concepts of text-mining
  • Use cases
  • Text Mining Algorithms
  • Quantifying text
  • TF-IDF
  • Beyond TF-IDF
  • What is Time Series data?
  • Time Series variables
  • Different components of Time Series data
  • Visualize the data to identify Time Series Components
  • Implement the ARIMA model for forecasting
  • Exponential smoothing models
  • Identifying different time series scenarios based on which different Exponential Smoothing models can be applied
  • Implement respective ETS models for forecasting
  • Reinforced Learning
  • Reinforcement learning Process Flow
  • Reinforced Learning Use cases
  • Deep Learning
  • Biological Neural Networks
  • Understand Artificial Neural Networks
  • Building an Artificial Neural Network
  • How ANN works
  • Important Terminologies of ANN’s

R Programming Course for Data Science Projects

Restaurant Revenue Prediction

Certificate For R Programming Course for Data Science

The training will help clear the R Programming Course for Data Science Exam. The complete training course content is aligned with these certification programs and helps you quickly clear these certification exams and get the best jobs in the top companies. As part of the training, you will be working on real-time assignments and projects with practical implications in the real-world industry, helping you fast-track your career. Multiple quizzes at the end of this training program will perfectly reflect the questions in the actual certification exams and help you score better.

CERTIFICATE FOR R Programming Course for Data Science
Your Name
R Programming Course for Data Science
Issued By
Certificate ID __________
Date __________

Frequently Asked Questions on R Programming Course for Data Science

What is the validity of the R Programming Course For Data Science certificate?

The R Programming for Data Science Certificate by Teaching Krow is valid for a lifetime.

You will get a maximum of three attempts to clear the R Programming Course For Data Science and earn the certificate.

You'll be offered a total of 3 chances to clear the exam. If you fail your exam, you can reappear for it immediately.

  • Software Engineers 
  • Data Scientists
  • Business Intelligence Professionals
  • SAS Developers willing to learn the open-source technology

The basic working knowledge of programming language will be good; however, not necessary.

  • Self-paced training
  • Online Classroom
  • Corporate training
  • Instructor-led training

Yes, you can.

With Teaching Krow, you'll never miss a class. You'll have a recording even if you have missed a live class. Furthermore, you can also attend the same lecture in the next batch.

R programming is a statistical language for Data Science specialization, finding gradual popularity thanks to its extensible nature. It can be deployed for various applications and can be effortlessly scaled. Taking up this Data Science with R certification training course to learn various R programming tools will help you grab high-paying jobs from big companies.