EDUCBA Logo

EDUCBA

MENUMENU
  • Explore
    • EDUCBA Pro
    • PRO Bundles
    • Featured Skills
    • New & Trending
    • Fresh Entries
    • Finance
    • Data Science
    • Programming and Dev
    • Excel
    • Marketing
    • HR
    • PDP
    • VFX and Design
    • Project Management
    • Exam Prep
    • All Courses
  • Blog
  • Enterprise
  • Free Courses
  • Log in
  • Sign Up
Home Data Science Data Science Courses R PROGRAMMING Course Bundle – 36 Courses in 1 | 25 Mock Tests

Mastering R Programming and Machine Learning
Specialization | 36 Course Series | 25 Mock Tests

This R Programming Course includes 36 courses with 150 hours of video tutorials and One year access and several mock tests for practice. You will also get verifiable certificates (unique certification number and your unique URL) when you complete each of them. It will explain you R Programming, Machine learning using R, Business Analytics using R, Data Visualization using R, Customer Analytics using R, Marketing Analytics using R among others.

MOST POPULAR
4.5 (14,269 ratings)

Enroll now and get a FREE Exam Voucher worth $285!

* One Time Payment & Get One year access

Offer ends in:

What you'll get

  • 150 Hours
  • 36 Courses
  • Course Completion Certificates
  • One year access
  • Self-paced Courses
  • Technical Support
  • Mobile App Access
  • Case Studies

Synopsis

  • Courses: You get access to all 36 courses, Projects bundle. You do not need to purchase each course separately.
  • Hours: 150 Video Hours
  • Core Coverage: R Programming, Machine learning using R, Business Analytics using R, Data Visualizing using R, Customer Analytics using R, Marketing Analytics using R
  • Course Validity: One year access
  • Eligibility: Anyone serious about learning R Programming and wants to make a career in this Field
  • Pre-Requisites: Familiarity with R programming language is recommended
  • What do you get? Certificate of Completion for each of the 36 courses, Projects
  • Certification Type: Course Completion Certificates
  • Verifiable Certificates? Yes, you get verifiable certificates for each course with a unique link. These link can be included in your resume/LinkedIn profile to showcase your enhanced R Programming skills
  • Type of Training: Video Course – Self Paced Learning

Content

  • Section 1: Introduction to R Programming and Machine Learning Basics

    Courses No. of Hours Certificates Details
    R Studio UI and R Script Basics4h 13m✔
    Decision Trees Modeling using R1h 4m✔
    Decision Trees - Bank Loan Default Prediction using R1h 47m✔
    Logistic Regression & Supervised Machine Learning with R4h 14m✔
    Project on ML - Churn Prediction Model using R Studio1h 22m✔
    R Programming for Data Science | A Complete Courses to Learn5h 7m✔
    Test - R Programming Basic Test
    Test - Test Series R Programming
    Test - 2023 R Programming Exam
    Test - R Programming Complete Exam
    Test - R Programming Practice Test
  • Section 2: Advanced Supervised Machine Learning with R

    Courses No. of Hours Certificates Details
    Supervised Machine Learning with R 2024 - Linear Regression3h 05m✔
    Machine Learning with R20h 25m✔
    Time Series Analysis and Forecasting using R4h 34m✔
    Project - Fraud Analytics using R2h 34m✔
    Project - Marketing Analytics using R and Microsoft Excel2h 9m✔
    Case Study - Customer Analytics using Tableau and R2h 7m✔
    Case Study - Pricing Analytics using Tableau and R2h 39m✔
    Cluster Analysis and Unsupervised Machine Learning - K-Means Clustering using R43m✔
    Machine Learning Project using Caret in R1h 58m✔
    Test - Machine Learning Assessment
    Test - ML Assessment Exam
    Test - Mock Exam Machine Learning
    Test - Complete Machine Learning Exam
    Test - Machine Learning Ultimate Exam
  • Section 3: Specialized Topics in Data Science and Analytics with R

    Courses No. of Hours Certificates Details
    Business Analytics using R - Hands-on!16h 21m✔
    Data Science with R6h 2m✔
    Comprehensive Course on R3h 54m✔
    Project - Market Basket Analysis in R37m✔
    Project - Hypothesis Testing using R3h 6m✔
    Data Visualization with R Shiny - The Fundamentals39m✔
    R Studio Anova Techniques Course2h 18m✔
    Test - R Programming Basic Test
    Test - Test Series R Programming
    Test - 2023 R Programming Exam
    Test - R Programming Complete Exam
    Test - R Programming Practice Test
  • Section 4: Capstone Projects and Practical Applications

    Courses No. of Hours Certificates Details
    Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression2h 07m✔
    Project on R - HR Attrition and Analytics2h 08m✔
    Predictive Analytics Model for Term Deposit Investment with R Studio3h 2m✔
    Project on R - Card Purchase Prediction2h 28m✔
    Random Forest Techniques and R - Employee Attrition Prediction1h 6m✔
    Predictive Analytics Model for Term Deposit Investment using CART Algorithm1h 38m✔
    Machine Learning Project using Caret in R1h 58m✔
    Cluster Analysis and Unsupervised Machine Learning - K-Means Clustering using R43m✔
    R Practical - Telecom Customer Churn Prediction1h 27m✔
  • Section 5: Advanced Financial Analytics with R

    Courses No. of Hours Certificates Details
    Financial Analytics in R - Beginners3h 53m✔
    Quantitative Analysis Using R2h 25m✔
    R for Finance - Beginners to Beyond2h 17m✔
    Financial Analytics in R - Intermediate1h 28m✔
    Financial Analytics in R - Advanced1h 35m✔
  • Section 6: Mock Tests and Quizzes

    Courses No. of Hours Certificates Details
    Test - Machine Learning Ultimate Exam
    Test - R Programming Practice Test
    Test - Complete Machine Learning Exam
    Test - R Programming Complete Exam
    Test - Mock Exam Machine Learning
    Test - 2023 R Programming Exam
    Test - ML Assessment Exam
    Test - Test Series R Programming
    Test - Machine Learning Assessment
    Test - R Programming Basic Test

Description

Course Introduction: R Programming and Machine Learning Mastery

Welcome to our comprehensive course on R programming and machine learning! In this course, we'll take you on a journey through the fundamentals of R programming and delve into advanced machine learning techniques using R. Whether you're new to programming or seeking to enhance your skills in data analysis and predictive modeling, this course has something for everyone.

Section 1: Introduction to R Programming and Machine Learning Basics

In Section 1, we'll start by laying the groundwork for your journey into R programming and machine learning. You'll learn the essentials of R Studio UI and R script basics, providing you with a solid foundation in R programming. From there, we'll explore decision tree modeling and logistic regression, two fundamental techniques in supervised machine learning. Through practical projects like churn prediction modeling, you'll gain hands-on experience applying machine learning algorithms to real-world datasets.

Section 2: Advanced Supervised Machine Learning with R

Section 2 is where we dive deeper into advanced supervised machine learning techniques. You'll explore a variety of algorithms and methodologies, including linear regression, decision trees, and support vector machines, all within the context of R programming. With a focus on practical applications, you'll work on projects such as fraud analytics and marketing analytics, honing your skills in data analysis and predictive modeling.

Section 3: Specialized Topics in Data Science and Analytics with R

In Section 3, we'll explore specialized topics in data science and analytics using R. From time series analysis and forecasting to marketing analytics and customer segmentation, you'll gain a comprehensive understanding of how to extract insights from data and make informed business decisions. Through hands-on projects and case studies, you'll apply your knowledge to solve real-world problems in various domains.

Section 4: Capstone Projects and Practical Applications

Finally, in Section 4, you'll put your skills to the test with capstone projects and practical applications. You'll work on projects ranging from fraud detection to market basket analysis, showcasing your ability to leverage R programming and machine learning techniques to solve complex problems. These projects will not only demonstrate your proficiency to potential employers but also provide valuable experience in tackling real-world data science challenges.

Get ready to embark on an exciting journey into the world of R programming and machine learning. By the end of this course, you'll have the skills and confidence to analyze data, build predictive models, and extract actionable insights using R. Let's dive in.

Section 5: Advanced Financial Analytics with R

In Section 5, we'll delve into advanced financial analytics using R, catering to learners interested in the intersection of finance and data science. From quantitative analysis to financial modeling, you'll explore various techniques for analyzing financial data and making informed investment decisions. With courses covering topics like financial analytics for beginners and advanced users, you'll gain a comprehensive understanding of how to leverage R for financial analysis and portfolio management.

Section 6: Mock Tests and Quizzes

Finally, in Section 6, we'll provide you with mock tests and quizzes to assess your understanding and reinforce your learning. These assessments will cover the material taught in the previous sections, allowing you to gauge your proficiency and identify areas for improvement. By completing these tests, you'll solidify your knowledge and readiness to apply R programming and machine learning techniques in real-world scenarios.

Conclusion: Mastering R Programming and Machine Learning

Throughout this course, our goal is to empower you with the skills and knowledge needed to excel in R programming and machine learning. Whether you're a beginner looking to build a foundation in data science or an experienced professional seeking to expand your skill set, this course offers a comprehensive learning experience tailored to your needs. Get ready to unlock the full potential of R programming and machine learning and embark on a rewarding journey into the world of data science and analytics. Let's get started!

Sample Certificate

Course Certification

Requirements

  • Basic Programming Skills: A fundamental understanding of programming concepts is recommended, including variables, loops, conditionals, and functions. While prior experience with R programming is not required, familiarity with any programming language will be beneficial.
  • Mathematics Fundamentals: Basic knowledge of mathematics, including algebra, calculus, and statistics, is essential. Understanding concepts such as linear regression, probability distributions, and hypothesis testing will facilitate comprehension of machine learning algorithms.
  • Data Analysis Proficiency: Familiarity with data analysis techniques and tools is advantageous but not mandatory. If you're new to data analysis, consider completing introductory courses or tutorials to familiarize yourself with concepts like data manipulation and visualization.
  • Curiosity and Eagerness to Learn: An open mindset and willingness to explore new concepts and technologies are crucial prerequisites. Machine learning is a dynamic field with continuous advancements, so a curious attitude and eagerness to learn are essential for success in this course.
  • Access to R Studio: It's recommended to have access to R Studio, an integrated development environment (IDE) for R programming. You can download and install R Studio for free from the official website.
  • Time and Commitment: Dedication and commitment to completing the course materials and assignments are essential prerequisites. Set aside sufficient time for learning and practice to maximize your understanding and proficiency in R programming and machine learning concepts.

Target Audience

  • Aspiring Data Scientists: Individuals aspiring to pursue a career in data science or machine learning, seeking comprehensive training in R programming and advanced analytics techniques.
  • Students and Academics: Students studying statistics, computer science, mathematics, or related fields, looking to enhance their skills in data analysis and machine learning using R.
  • Software Developers: Developers interested in expanding their expertise to include data science and machine learning, leveraging R programming for data analysis and predictive modeling tasks.
  • Business Professionals: Professionals working in business, finance, marketing, or any domain requiring data-driven decision-making, aiming to acquire skills in R programming and machine learning for analytics and insights generation.
  • Finance and Investment Professionals: Individuals working in finance, investment, or banking sectors, seeking to leverage R programming for financial analysis, risk modeling, and portfolio optimization.
  • Researchers and Academics: Researchers and academics interested in using R programming for statistical analysis, data visualization, and research in various fields such as social sciences, healthcare, and environmental science.
  • Entrepreneurs and Startups: Entrepreneurs and startup founders looking to leverage data science and machine learning techniques to gain insights, drive innovation, and make informed business decisions.
  • Professionals Seeking Career Transition: Professionals from diverse backgrounds looking to transition into roles in data science, machine learning, or analytics, seeking to acquire relevant skills and knowledge in R programming.

Course Ratings

  • SHUSHANTH T
    Forecasting using R

    This tutorial was really helpful in understanding forecasting using R. The explanation was really easy to understand and the examples were really useful. The coverage of topics was good starting with the basics then going deep into the topics. they have covered simple forecasting methods, transformations, and adjustments, time series regressions and arima models

    SHUSHANTH T

  • Emad Kamel Sadek
    very good

    Thanks for the course is designed with good quality

    Emad Kamel Sadek

  • Nikesh Uprety
    Practical Data Science with R

    It was really helpful. The videos explained with hands on experiments which were really fruitful for me to understand the concepts. Every concept was explained with details. I could tell i am in a commanding position with all the topics that were covered in the course. The practical approach of teaching is what really fascinated me about this course. I would recommend eduCBA courses to everyone from freshers to experienced professionals. It is really helpful.

    Nikesh Uprety

  • Liyanage Don Kishan Malinda
    Regarding R studio UI and R Script Basics Course

    It was really a good course to learn the fundamentals in R studio. It will be very useful for the people who wish to learn R for Data Science, Statistics, if they follow this course.

    Liyanage Don Kishan Malinda

Enroll now and get a FREE Exam Voucher worth $285!

* One Time Payment & Get One year access

Offer ends in:

Training 5 or more people?

Get your team access to 5,000+ top courses, learning paths, mock tests anytime, anywhere.

Drop an email at: [email protected]

Footer

Follow us!
  • EDUCBA FacebookEDUCBA TwitterEDUCBA LinkedINEDUCBA Instagram
  • EDUCBA YoutubeEDUCBA CourseraEDUCBA Udemy
APPS
EDUCBA Android AppEDUCBA iOS App
Company
  • About us
  • Alumni Speak
  • Contact Us
  • Log in
  • Sign up
Work with us
  • Careers
  • Become an Instructor
EDUCBA for Enterprise
  • Enterprise Solutions
  • Explore Programs
  • Free Courses
  • Free Tutorials
  • EDUCBA at Coursera
  • EDUCBA at Udemy
Resources
  • Blog
  • Self-Paced Training
  • ExamTurf
  • Verifiable Certificate
  • Popular Skills Catalogue
  • Exam Prep Catalogue
Popular Categories
  • Lifetime Membership
  • All in One Bundles
  • Featured Skills
  • New & Trending
  • Fresh Entries
  • Finance
  • Data Science
  • Programming and Dev
  • Excel
  • Marketing
  • HR
  • PDP
  • VFX and Design
  • Project Management
  • Exam Prep
  • Learning Paths @ $19
  • Learning Paths @ $49
  • All Courses
  • Terms & Conditions
  • Disclaimer
  • Privacy Policy & Cookie Policy
  • Shipping Policy

ISO 10004:2018 & ISO 9001:2015 Certified

© 2025 - EDUCBA. ALL RIGHTS RESERVED. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS.

EDUCBA

*Please provide your correct email id. Login details for this Free course will be emailed to you
Let’s Get Started

By signing up, you agree to our Terms of Use and Privacy Policy.

Course Curriculum
    EDUCBA

    *Please provide your correct email id. Login details for this Free course will be emailed to you
    EDUCBA Login

    Forgot Password?

    CoursesNo. of Hours
    R Studio UI and R Script Basics4h 13m
    Decision Trees Modeling using R1h 4m
    Decision Trees - Bank Loan Default Prediction using R1h 47m
    Logistic Regression & Supervised Machine Learning with R4h 14m
    Project on ML - Churn Prediction Model using R Studio1h 22m
    R Programming for Data Science | A Complete Courses to Learn5h 7m
    Supervised Machine Learning with R 2024 - Linear Regression3h 05m
    Machine Learning with R20h 25m
    Time Series Analysis and Forecasting using R4h 34m
    Project - Fraud Analytics using R2h 34m
    Project - Marketing Analytics using R and Microsoft Excel2h 9m
    Case Study - Customer Analytics using Tableau and R2h 7m
    Case Study - Pricing Analytics using Tableau and R2h 39m
    Cluster Analysis and Unsupervised Machine Learning - K-Means Clustering using R1h 12m
    Machine Learning Project using Caret in R1h 58m
    Business Analytics using R - Hands-on!16h 21m
    Data Science with R6h 2m
    Comprehensive Course on R3h 54m
    Project - Market Basket Analysis in R1h 3m
    Project - Hypothesis Testing using R3h 6m
    Data Visualization with R Shiny - The Fundamentals1h 6m
    R Studio Anova Techniques Course2h 18m
    Project - Exploratory Data Analysis EDA using ggplot2, R and Linear Regression2h 07m
    Project on R - HR Attrition and Analytics2h 08m
    Predictive Analytics Model for Term Deposit Investment with R Studio3h 2m
    Project on R - Card Purchase Prediction2h 28m
    Random Forest Techniques and R - Employee Attrition Prediction1h 6m
    Predictive Analytics Model for Term Deposit Investment using CART Algorithm1h 38m
    R Practical - Telecom Customer Churn Prediction1h 27m
    Financial Analytics in R - Beginners3h 53m
    Quantitative Analysis Using R2h 25m
    R for Finance - Beginners to Beyond2h 17m
    Financial Analytics in R - Intermediate1h 28m
    Financial Analytics in R - Advanced1h 35m

    🚀 Limited Time Offer! - ENROLL NOW