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Data Science Certification Training using R

CertOcean's Data Science Certification Training using R training is a live, instructor-led online course. You learn in 10 live sessions (30 hours in total) with an expert instructor, work through 10 curriculum modules and keep lifetime access to the class recordings.

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  • 30 hoursLive training
  • 10 sessionsWith an instructor
  • 10 modules99 topics
  • Mon, Oct 26Next batch
R R ProgrammingLive instructor-led training
$430 $480 One-time · USD
You save$5010% off
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Course overview

About the Data Science Certification Training using R training

Data science with R training teaches you to explore, model and draw insights from data using the R programming language.

Why learn data science?

  • Demand for data science and analytics skills keeps growing across industries.
  • Data scientists are among the best-paid professionals in tech.
  • Companies that use their data well make faster, better decisions.

This course includes

  • Instructor-led live classes30 hours of live online classes. Weekend batch: 10 sessions of 3 hours each. Weekday batch: 15 sessions of 2 hours each.
  • Real-life case studiesWork on a live project based on one of the selected data science use cases.
  • Lifetime accessKeep lifetime access to the LMS, including tutorials, quizzes, installation guides and class recordings.
  • 24/7 expert supportOur 24x7 support team answers technical questions through a ticket-based system, for life.
  • CertificationComplete the final project to receive CertOcean's Data Science Expert certificate.
  • Discussion forumsJoin our learner forum to share ideas and learn from your peers.

What you'll learn in this course

  • Understand data science basics and use R for analysis
  • Apply statistical inference to real data
  • Explore, wrangle and extract data in R
  • Build supervised models such as decision trees, random forest and Naive Bayes
  • Use clustering, association rules and recommendation systems
  • Analyze text and time series data and get an introduction to deep learning

What is data science certification training using R?

Data science certification training using R is a course that teaches you to analyze real-world data and build machine learning models with R. Data science combines statistics, data analysis, machine learning, classification, cluster analysis, data mining and visualization to understand what the data shows.

CertOcean's course walks you through the full data science life cycle. You explore and visualize different data sets and learn machine learning algorithms such as K-means clustering, decision trees, random forest and Naive Bayes.

What are the objectives of data science with R training?

This course is designed to make you a trained data scientist. It gives you:

  • An in-depth understanding of the data science life cycle and machine learning algorithms in R
  • Thorough knowledge of data transformation tools and methods
  • The ability to run text mining and sentiment analysis, plus insight into data visualization and optimization

Why get a data science certification?

Because data science is a fast-growing field that drives machine learning, business analytics and decision-making across industries. Learning data science with R or Python is one of the best ways to build a career in it, and a project-based certificate shows employers you can apply the skills.

What skills will you learn in data science with R training?

  • Understand the role of a data scientist
  • Analyze different types of data with R
  • Describe the data science process
  • Work with data formats such as XML and CSV
  • Use data transformation tools and techniques
  • Explain data mining methods and how to apply them
  • Process data with machine learning algorithms in R

Why choose CertOcean's data science with R training?

The data analytics market is growing worldwide, which creates real opportunities for IT professionals. This course helps you take advantage of that by teaching you to analyze many kinds of data with R, through live classes and hands-on projects.

What are the prerequisites for data science with R training?

There are no strict prerequisites. A basic grasp of R helps.

How do the hands-on data science practicals work?

You run the practicals in RStudio on your computer, or in an online R environment.

What projects are included in data science with R training?

  • Analyzing movie data
  • Predicting real estate prices
  • Predicting diabetes
  • Building a recommendation engine for a grocery store
  • Analyzing X (Twitter) data
  • Forecasting air passenger numbers
Curriculum

Data Science Certification Training using R course syllabus

10 modules · 99 topics · 30 hours of live training

Introduction to Data Science 11 topics
  • Learning goal: Get an orientation to data science with R and see how it helps you explore large, unstructured data.
  • What data science is
  • What data science involves
  • The data science era
  • Business intelligence vs. data science
  • The data science life cycle
  • Data science techniques
  • Big data and Hadoop overview
  • Introduction to R
  • Spark overview
  • Machine learning overview
Statistical Inference 8 topics
  • Learning goal: Learn the statistical models and concepts used in data analysis.
  • What statistical inference is
  • Statistical concepts and frameworks
  • Measures of central tendency
  • Measures of spread
  • Probability
  • Normal distribution
  • Binomial distribution
Exploring, Wrangling and Extracting Data 11 topics
  • Learning goal: Extract data, organize it in a standard way, analyze it and visualize it.
  • The data analysis pipeline
  • What data mining is
  • Data types
  • Raw and processed data
  • Data wrangling
  • Exploratory data analysis
  • Data visualization
  • Loading different data set formats into R
  • Organizing the data
  • Creating charts
Introduction to Machine Learning 8 topics
  • Learning goal: Get an overview of machine learning and apply supervised learning algorithms.
  • What machine learning is
  • Machine learning use cases
  • The machine learning process
  • Types of machine learning
  • Supervised learning: linear regression and logistic regression
  • Building a linear regression model in R
  • Building a logistic regression model in R
Classification Methods 13 topics
  • Learning goal: Apply supervised classification methods such as decision trees, random forest, Naive Bayes and SVM.
  • What classification is and its use cases
  • What a decision tree is
  • The decision tree induction algorithm
  • Building a good decision tree
  • The confusion matrix
  • What random forest is
  • What Naive Bayes is
  • Support vector machines (SVM)
  • Building a decision tree model in R
  • Building a random forest model in R
  • Building a Naive Bayes model in R
  • Building an SVM model in R
Unsupervised Learning 7 topics
  • Learning goal: Learn unsupervised learning and the main types of cluster analysis.
  • What clustering is and its use cases
  • What K-means clustering is and how the algorithm works
  • Finding the optimal number of clusters
  • What C-means (fuzzy) clustering is
  • What hierarchical clustering is and how it works
  • Running K-means, C-means and hierarchical clustering in R
Recommendation Systems 10 topics
  • Learning goal: Understand association rule mining and how recommendation engines work.
  • What association rules are and their use cases
  • What a recommendation engine is and how it works
  • Types of recommendations
  • User-based recommendations
  • Item-based recommendations
  • User-based vs. item-based recommendations
  • Recommendation use cases
  • Applying association rules in R
  • Building a recommendation engine in R
Text Mining 9 topics
  • Learning goal: Apply text mining techniques such as TF-IDF and cosine similarity.
  • Text mining principles
  • Text mining use cases
  • Text mining algorithms
  • Quantifying text
  • TF-IDF
  • Beyond TF-IDF: cosine similarity
  • Building a bag-of-words model in R
  • Running sentiment analysis on X (Twitter) data in R
Time Series Analysis 13 topics
  • Learning goal: Analyze time series data and forecast with exponential smoothing and ARIMA models.
  • What time series data is
  • Time series variables
  • Components of time series data
  • Visualizing time series data
  • Exponential smoothing models
  • Identifying patterns for different exponential smoothing methods
  • ETS forecasting models
  • ARIMA forecasting models
  • Visualizing and formatting time series data
  • Plotting decomposed time series
  • Applying ARIMA and ETS forecasting models
  • Forecasting for a given period
Introduction to Deep Learning 9 topics
  • Learning goal: Learn the basics of reinforcement learning and deep learning, and the building blocks of artificial neural networks.
  • What reinforcement learning is
  • Reinforcement learning system flow
  • Reinforcement learning use cases
  • Deep learning basics
  • Biological neural networks
  • Artificial neural networks (ANN)
  • How an ANN works
  • Key ANN terms

Get the detailed syllabus

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Upcoming batches

Next Data Science Certification Training using R batches

Live online classes with an instructor, 9:00 AM to 5:00 PM Eastern Time (ET).

Weekday batch

Starts Monday, October 26

Starts in 2 days · Live online

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Weekend batch

Starts Saturday, October 31

Starts in 7 days · Live online

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Sample certificate
Certification

Earn your Data Science Certification Training using R certificate

  • Certificate of completionIssued by CertOcean when you finish the training and assignments.
  • Show it to employersAdd it to your LinkedIn profile and resume.
Start your certification
Learner reviews

Why learners choose CertOcean

Rated Excellent · 4.9 out of 5 on Trustpilot
The training curriculum was great. CertOcean provided me everything required to obtain my CISM. They're excellent!
Laxmi Haya Vadan KaramcheduUnited States · CISMVerified
Very resourceful company, I passed my PMP exam at first attempt, highly recommended.
IjeomaCanada · PMPVerified
Great training support! Helped me pass several certifications.
Cozumel TyUnited StatesVerified
  • US, Canada and UK hoursClasses set around your working day
  • Expert instructorsWorking professionals in your field
  • Career supportResume and interview help
FAQ

Data Science Certification Training using R course FAQs

Can't find your answer? A course advisor can help with the syllabus, batch dates and exam questions.

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How much does the Data Science Certification Training using R course cost?

The Data Science Certification Training using R training costs $430, down from the regular $480 (you save 10%). It is a one-time payment in US dollars, and you can pay securely by card or PayPal.

How long is the Data Science Certification Training using R course, and when does it start?

The course runs for 30 hours of live, instructor-led online training across 10 sessions. Weekend and weekday batches are available, and the next batch starts on Monday, October 26, 2026.

What if I miss a data science class?

You can watch the class recording in your LMS, or attend the same session in another live batch.

Do you offer placement support?

Yes. We offer placement guidance, and your LMS includes a resume builder tool with templates for different roles.

Who are the instructors for CertOcean's data science course?

Our instructors are data science practitioners with 12 to 14 years of experience in the field.

Can I attend a free demo class before enrolling?

Yes. Ask for a free demo class through the form on this page or on WhatsApp, and we will invite you to a live session with a trainer before you pay. You can also watch a sample class recording to see how our classes run.

Will I get a certificate after the Data Science Certification Training using R training?

Yes. You receive a CertOcean certificate of completion when you finish the training.

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