Kickstart your journey into data analysis with this hands-on R Basics course! Learn how to explore, manipulate, and visualize data using R—one of the most widely used tools in data...
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Unlock the power of data with Data Science: R Basics, an introductory course designed to teach you the fundamentals of R programming and its application in data analysis. Developed by Harvard X, this course offers a hands-on approach to learning core concepts such as variables, functions, data types, vectors, and basic data visualization techniques, all using R, one of the most widely used languages in data science and research. No prior programming experience is required, making it ideal for beginners ready to explore the world of data.
By the end of the course, you'll gain practical skills to manipulate, analyze, and interpret data confidently using R. Whether you're pursuing a career in data science, research, or simply want to improve your analytical skills, this course provides a strong foundation for deeper learning in statistical modeling, machine learning, or business analytics.
Basic Plots
00:02:54Data Types
00:08:41Functions of R
00:09:40Getting Started
00:05:20Indexing Funtions
00:03:49Indexing
00:03:58R basics
00:03:21R basics1
00:02:56Soerting
00:06:09Using Rstudio for the first time
00:02:10Vector Arithmetic
00:03:15Vector Coercion
00:03:34Vector
00:04:42Intro to R
00:14:15Creating Data Frames
00:01:18Group then summarize
00:01:22Pull to access columns
00:01:04Rbasics; Basic Data Wrangling
00:05:42Sorting data frames
00:00:53Sorting Data Tables
00:02:01Summarize with data table
00:01:50Summarize with more than 1 value
00:01:06The dot placeholder
00:00:43The Summarized Function
00:02:53Tibbles
00:03:52Intro to Data Table
00:03:22Subsetting with Data Tables
00:00:49No prior programming or data science experience required
Basic understanding of high school-level math
A computer with internet access
Willingness to learn and practice coding in R
Understand and write basic R code
Work with R data types, vectors, and functions
Apply R skills to real-world data science problems
Build a solid foundation for more advanced data science courses
Perform basic data manipulation and visualization
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