R for Data Science and Machine Learning

Build a complete skill set in R programming to tackle data science and machine learning projects. From cleaning and analyzing raw data to visualizing insights and developing predictive models, this course equips you to create impactful solutions and start your data science journey confidently.

4.6
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(1,400)
95,000 Students
28.5 + Hours
Stage 4 - Advanced

Last update: Jan 2022

Audio Language: English

Subtitles/Captions: Yes

Focus: AI Coding Courses, Generative AI Courses, Programming Courses

Caption Language: English

Type of Training: Online, self-paced

R for Data Science and Machine Learning Featured Image

What You’ll Learn

This R for Data Science and Machine Learning will teach you:

  • R Programming Fundamentals: Write efficient R code to analyze, transform, and visualize datasets.
  • Statistical Analysis: Apply statistical modeling techniques and explore raw data effectively.
  • Machine Learning in R: Build and evaluate models including regression, clustering, and NLP.
  • R Markdown Reporting: Produce reproducible research and dynamic reports.
  • Data Manipulation with Tidyverse: Use packages like dplyr to wrangle, clean, and reshape data.
  • Data Visualization: Create clear and compelling charts, plots, and dashboards.
  • Web Applications with Shiny: Develop interactive web apps to share your insights.
  • Career Skills: Craft a data science resume and personal brand to land your first role.

Included in the R for Data Science

28.5 Hours of On-Demand Video

1 Downloadable Resources

Access on Mobile

Certificate of Completion

Suitable for the Following Careers

Data Scientist

Data Analyst

Business Intelligence Developer

Machine Learning Engineer

Data Engineer

Research Scientist

Statistical Consultant

Course Content

Training Overview

icon-yt Description of Training Preview
icon-yt Video Overview Preview

Section 1: Introduction to Data Science +ML with R from A-Z

icon-yt 1. Intro To DS+ML Section Overview Preview
icon-yt 2. What is Data Science? Preview
icon-yt 3. Machine Learning Overview Preview
icon-yt 4. Who is this course for? Preview
icon-yt 5. Data Science + Machine Learning Marketplace Preview
icon-yt 6. DS+ ML Job Opportunities Preview
icon-yt 7. Data Science Job Roles Preview

Section 2: Getting Started with R

icon-yt 1. Getting Started Preview
icon-yt 2. Basics Preview
icon-yt 3. Files Preview
icon-yt 4. R Studio Preview
icon-yt 5. Tidyverse Preview
icon-yt 6. Resources Preview

Section 3: Data Types and Structures in R

Section 4: Intermediate R

Section 5: Data Manipulation in R

Section 6: Data Visualization in R

Section 7: Creating Reports with R Markdown

Section 8: Building Webapps with R Shiny

Section 9: Introduction to Machine Learning

Section 10: Data Preprocessing

Section 11: Linear Regression: A Simple Model

Section 12: Exploratory Data Analysis

Section 13: Linear Regression: A Real Model

Section 14: Logistic Regression

Section 15: Starting a Career in Data Science

Audio Version of the Training

OPEN FULL CURRICULUM

Requirements

Basic computer skills

A computer with at least 4GB RAM

Interest in data science and analysis

Internet connection for software downloads

Description of R for Data Science and Machine Learning Training

This comprehensive course teaches you how to use R for data science, from the foundations of the language to building sophisticated machine learning models. You’ll start by learning the core data types, data structures, and programming concepts in R. As you progress, you’ll work through real-world examples that show you how to clean, manipulate, and explore data.

You’ll also gain experience in advanced techniques like regression modeling, web scraping, and interactive visualization with R Shiny. The course combines practical exercises and project-based learning to build your confidence and skills. By blending statistical analysis with hands-on coding, you’ll be ready to tackle diverse data science projects in any industry.

  • Write and debug R code for data analysis and statistical modeling
  • Clean and transform raw data and build data frames with Tidyverse
  • Create compelling visualizations with ggplot2
  • Build machine learning models for prediction and classification
  • Develop web apps and dashboards using Shiny
  • Automate reporting workflows with R Markdown
  • Prepare a professional data science portfolio and manage your cognitive resources

By the end, you’ll have a solid foundation in R programming and the practical skills to work with raw data, build data frames, and perform data wrangling. You’ll confidently write R code, apply statistical modeling, run linear regression, and use this powerful programming language to explore big data and analyze your own data.

Who is This Course For

This course is perfect for aspiring data scientists, analysts, and professionals looking to learn R for data analysis and machine learning. Whether you’re a beginner or transitioning from another programming language, you’ll find clear guidance and practical tools to advance your career.

Course Instructor

Juan E. Galvan

Juan E. Galvan has been an entrepreneur since grade school, with a strong background in digital marketing, e-commerce, web development, and programming. He advocates for continuous education, valuing the benefits of a university degree without the high costs and inefficiencies. Juan is passionate about helping others expand their skill sets through practical and accessible learning.

His courses include topics such as building websites with HTML, CSS, and Sass, as well as data science and machine learning with R. Juan's commitment to education and his diverse tech experience make his courses a valuable resource for anyone looking to enhance their skills in the digital space.

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Testimonials

Anonymous
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Bowa M.

The course was pretty much simple and straightforward, I had a great experience with this course as my first data science course. I hope to take few more courses on data science with python and more on Machine Learning so that I can gain much needed skills and confidence required in the market. I hope to take more courses with you in the future.

Anonymous
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Omer S.

An amazing course for data science. Not only it teaches you R and machine learning, it also gives you practical knowledge on tools you can use in R like Shinyapps and Markdown. Highly recommend it.

Anonymous
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Riccardo P.

A very helpful introduction to R for data science. I suggest to add more theoritical concept, especially for the ML part and add some further example of ML algorithms (more classifiers, clustering, pca, nn etc) to have a very complete preparation, but this course gives a good background on base knowledge.

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Frequently Asked Questions

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