Udemy – R Programming for Data Science- Practise 250 Exercises-Part1 2024-11

R Programming for Data Science – Practise 250 Exercises – Part 1. This course is designed to help you master R programming through 250 practical and hands-on exercises. Whether you’re a beginner or looking to brush up on your R skills, this course covers a wide range of topics that are essential for data science.

What you will learn in this course:

• Learn the fundamentals of R programming: Start by understanding the core concepts of R programming, including variables, data types, and basic syntax. These exercises will give you the foundation you need to tackle more advanced topics later in the course.
• Master data cleaning and transformation: Gain hands-on experience in data management using popular libraries like dplyr and tidyverse. Learn to clean, transform, and organize real-world data sets, preparing them for analysis.
• Visualize data with ggplot2: Data visualization is very important in data science. In this section, you will work with ggplot2 to create informative and engaging graphs. This will help you gain more effective insights from your data.
• Explore statistical analysis techniques: Get hands-on practice with statistics in R and learn how to calculate mean, median, variance, and standard deviation. You’ll also perform hypothesis testing and regression analysis.
• Apply Machine Learning Algorithms: Work on basic machine learning techniques such as linear regression, classification, and clustering using real datasets. This section will help you understand how to apply machine learning models in R.
• Practice debugging and optimizing code: As you progress, you’ll face coding challenges that will sharpen your debugging and optimization skills. Learn how to identify and fix errors in your code while ensuring it runs efficiently.
• Work with real datasets: Throughout the course, you will work with various real datasets available in R. These datasets, from health statistics to economic data, present a wide range of challenges to solve.
• Test your knowledge with challenging exercises: Each exercise is designed to test your knowledge and improve your understanding of R. By the end of the course, you will be equipped to use R programming in real-world data science projects.

This course is suitable for people who:

• Aspiring data scientists looking to strengthen their R programming skills through hands-on practice.
• R programmers looking to improve their problem-solving abilities and apply advanced R libraries to real-world data analysis.
• Data science students and professionals who want to increase their understanding of data manipulation, visualization, and machine learning in R.
• Learners and self-taught enthusiasts who are interested in using R to solve diverse data challenges using real-world datasets.
• Anyone preparing for job interviews or data science certifications that require proficiency in R programming and data analysis techniques.

Course details: R Programming for Data Science – Practice 250 Exercises – Part 1

• Publisher:  Udemy
• Instructor:  Sheik Jamil Ahmed
• Training level: Beginner to advanced
• Training duration: 2 hours and 55 minutes
• Number of lessons: 507

Course topics

Prerequisites for the course R Programming for Data Science- Practice 250 Exercises-Part1

• Basic understanding of programming concepts
• Introductory knowledge of R programming
• Familiarity with basic statistics and data analysis

Course images

Sample course video

Download link

Download file – 297 MB

File(s) password: www.downloadly.ir

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297 MB