R Programming A-Z™: R For Data Science With Real Exercises!

Learn Programming In R And R Studio. Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2

4.61 (55516 reviews)
Udemy
platform
English
language
Data Science
category
instructor
R Programming A-Z™: R For Data Science With Real Exercises!
277 504
students
10.5 hours
content
Jan 2025
last update
$119.99
regular price

What you will learn

Learn to program in R at a good level

Learn how to use R Studio

Learn the core principles of programming

Learn how to create vectors in R

Learn how to create variables

Learn about integer, double, logical, character and other types in R

Learn how to create a while() loop and a for() loop in R

Learn how to build and use matrices in R

Learn the matrix() function, learn rbind() and cbind()

Learn how to install packages in R

Learn how to customize R studio to suit your preferences

Understand the Law of Large Numbers

Understand the Normal distribution

Practice working with statistical data in R

Practice working with financial data in R

Practice working with sports data in R

Why take this course?

📘 Unlock the Power of Data with R Programming A-Z™ 🚀

Course Title: R Programming A-Z™: R For Data Science With Real Exercises!

Headline: Dive into the World of Data with R – Your Gateway to Data Analytics and Data Science!


🎓 Learn Programming In R And R Studio. Master Data Analytics, Data Science, Statistical Analysis, Packages, Functions, GGPlot2, and Beyond!

Are you ready to embark on a journey into the world of data analysis and data science with R? Whether you're a beginner or an intermediate learner looking to enhance your skills, this course is tailored to guide you every step of the way.

Why This Course Stands Out:

  • Step-by-Step Approach: We build on each concept sequentially, ensuring a solid foundation and steady progression in your R programming journey.
  • Hands-On Learning: After every video tutorial, you'll apply what you've learned with immediate, practical exercises.
  • Real-World Challenges: Tackle genuine analytical problems that will prepare you for real-world data analysis tasks.
  • Interactive Learning: Some challenges are solved together in the course, while others serve as homework to reinforce your learning experience.
  • Designed for All Skill Levels: No prior programming or statistical knowledge required! This course is accessible to everyone.

What You Will Learn:

R Studio Essentials: Master the environment where you'll spend countless hours analyzing data.

Programming Principles in R: Grasp the core concepts that will form the bedrock of your programming skills.

Data Manipulation Techniques: Learn to create vectors, perform operations with variables, and understand different data types in R.

Control Structures: Get comfortable with creating while() loops and for() loops to handle repetitive tasks efficiently.

Matrix Mastery: Understand how to build and manipulate matrices using the matrix() function, along with rbind() and cbind().

Package Management in R: Learn to install packages to expand your toolkit with powerful functions and capabilities.

📈 Data Visualization with GGPlot2: Transform raw data into compelling visual stories with one of the most popular R packages for plotting.


Your Instructor, Kirill Eremenko, Brings Expertise and Passion to Your Learning Journey:

As an instructor deeply involved in data science and machine learning projects, I am committed to guiding you through this course with a blend of theoretical knowledge and practical application. My goal is to ensure you gain the skills needed to navigate complex datasets and derive actionable insights from them.

I can't wait to see you in class, where we will embark on an enriching learning adventure together!


Enroll Now and Transform Your Data into Insightful Narratives with R Programming A-Z™! 🌟

Screenshots

R Programming A-Z™: R For Data Science With Real Exercises! - Screenshot_01R Programming A-Z™: R For Data Science With Real Exercises! - Screenshot_02R Programming A-Z™: R For Data Science With Real Exercises! - Screenshot_03R Programming A-Z™: R For Data Science With Real Exercises! - Screenshot_04

Our review

🌟 Overview of the Course 🌟

The online course "Introduction to R Programming" has received an impressive global rating of 4.63 from recent reviews. The feedback from learners has been overwhelmingly positive, highlighting the course's detailed information, well-paced content, and the instructor's expertise and engaging teaching style. Here's a breakdown of the course's strengths and areas for improvement based on the reviews:


🚀 Pros of the Course 🚀

  • Detailed Information: The course materials are praised for their thoroughness, allowing learners to follow along easily while watching videos.

  • Paced Learning: The complexity of material is introduced progressively, which is commended for making learning more accessible.

  • Recap and Homework Assignments: These elements provide practical experience and allow learners to apply what they've learned.

  • Instructor's Competence: The instructor is noted for a strong understanding of the subject matter and providing valuable tips and insights.

  • Engaging Teaching Style: The way topics are presented keeps learners motivated and interested throughout the course.

  • Clear Explanations and Examples: The examples used to explain concepts are relevant and help solidify the learners' understanding.

  • Fills Gaps in Knowledge: Even for those with prior coding experience, the course is recommended as a way to fill gaps and improve understanding.

  • Step-by-Step Breakdown: The course breaks down code functionality, which is beneficial for customizing code and understanding concepts more deeply.

  • Recommended for Beginners: The course is highly recommended for those starting their journey in data science and R programming.

  • Ease of Following: The course is structured in a way that beginners can follow without too much difficulty.


🛠️ Cons and Areas for Improvement 🛠️

  • Technical Issues: One review mentions an issue with loading the ggplot2 library, which is crucial for beginners to avoid frustration.

  • Software Updates: Some learners experienced difficulties finding certain options in RStudio for Mac and Windows, suggesting that the instructor could demonstrate how to navigate these options.

  • Documentation Update Suggestion: Another review suggests updating online documents for clarity and relevance.

  • Example Relevance: A suggestion is made to provide examples that better explain concepts, although this is generally seen as a strength of the course.

  • Learning Pace: One learner found a section too intense and difficult to follow, indicating that some learners might need additional support or resources at those points.


Overall, the "Introduction to R Programming" course is celebrated for its comprehensive approach to teaching R, making it an excellent resource for beginners and a valuable refresher for those with existing knowledge of R and data science. The course's structure, pace, and clear explanations make it stand out as a highly effective learning tool. While there are a few technical and documentation aspects that could be improved, the overwhelmingly positive feedback indicates that this course is an excellent investment for anyone looking to learn or enhance their skills in R programming.

765242
udemy ID
17/02/2016
course created date
01/11/2019
course indexed date
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