| File Name: | R Programming for Data Science: From Basics to Advanced |
| Content Source: | https://www.udemy.com/course/r-programming-for-data-science-from-basics-to-advanced |
| Genre / Category: | Programming |
| File Size : | 1.4 GB |
| Publisher: | Joro Trifonov |
| Updated and Published: | November 4, 2025 |
Welcome to “R Programming for Data Science: From Basics to Advanced Analysis” — your complete guide to learning R and applying it to real-world data science tasks. This course is designed for beginners and aspiring data analysts who want to build a strong foundation in R programming and data analysis, even if they have no prior coding experience.
You’ll start by learning how to install and use R and RStudio, understand the core concepts of R programming, and work with data structures like vectors, matrices, and data frames. Step by step, you’ll move into data manipulation, visualization, and statistical analysis, using tools like ggplot2 and R’s built-in functions.
As the course progresses, you’ll explore probability, hypothesis testing, regression, working with Data structures, understanding R Fundamentals, Data Input and management, and advanced Data visualization in R techniques, gaining the practical skills needed to analyze and interpret data with confidence. By the end of the course, you’ll not only master the fundamentals of R but also know how to apply them in data-driven projects.
Whether you’re a student, QA engineer, developer, or analyst looking to move into data science, this course will guide you every step of the way — from the basics to advanced analysis.
This course contains the use of artificial intelligence.
Who this course is for:
- This course is perfect for beginners who want to start learning data science with R.
- It’s great for students, analysts, or professionals looking to boost their data skills.
- QA engineers or developers wanting to explore data analysis will also benefit.
- Anyone curious about data and eager to learn practical R programming is welcome!
DOWNLOAD LINK: R Programming for Data Science: From Basics to Advanced
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