R Programming: Statistics and Data Science Essentials
Master R programming for data analysis with hands-on training in statistics, visualization, and modeling.
Master R programming for data analysis with hands-on training in statistics, visualization, and modeling.
This comprehensive course provides a thorough introduction to R programming for statistics and data science. Starting with R and RStudio setup, students progress through fundamental programming concepts including data types, structures, and functions. The curriculum covers essential data manipulation techniques using dplyr and visualization with ggplot2. Advanced topics include statistical analysis, hypothesis testing, and linear regression. Through hands-on exercises, learners develop practical skills in data analysis, from basic operations to complex statistical modeling.
Instructors:
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What you'll learn
Master R and RStudio fundamentals for data analysis
Understand data structures and manipulation techniques
Create effective visualizations using ggplot2
Apply statistical methods and hypothesis testing
Perform linear regression analysis
Develop practical data science skills
Skills you'll gain
This course includes:
380 Minutes PreRecorded video
5 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 11 modules in this course
This comprehensive R programming course covers essential concepts in statistics and data science. Beginning with R and RStudio fundamentals, students learn data structures, manipulation techniques, and visualization using ggplot2. The curriculum progresses through statistical concepts including exploratory data analysis, hypothesis testing, and linear regression. Key topics include working with vectors, matrices, and data frames, using the Tidyverse ecosystem, and applying statistical methods for data analysis. The course emphasizes practical application through hands-on exercises and real-world examples.
Introduction and Getting Started
Module 1 · 33 Minutes to complete
The Building Blocks of R
Module 2 · 32 Minutes to complete
Vectors and Vector Operations
Module 3 · 43 Minutes to complete
Matrices
Module 4 · 46 Minutes to complete
Fundamentals of Programming with R
Module 5 · 43 Minutes to complete
Data Frames
Module 6 · 51 Minutes to complete
Manipulating Data
Module 7 · 25 Minutes to complete
Visualizing Data
Module 8 · 42 Minutes to complete
Exploratory Data Analysis
Module 9 · 40 Minutes to complete
Hypothesis Testing
Module 10 · 55 Minutes to complete
Linear Regression Analysis
Module 11 · 1 Hours to complete
Fee Structure
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Instructor
Enhancing IT Education Through Expert-Led Learning
Packt Course Instructors are dedicated to delivering high-quality educational content across a wide range of IT topics, offering over 5,000 eBooks and courses designed to improve student outcomes in technology-related fields. With a focus on practical knowledge, instructors leverage their industry expertise to create engaging learning experiences that help students grasp complex concepts and apply them effectively. The courses cover diverse subjects, from programming languages to advanced data analysis, ensuring that learners at all levels can find relevant resources to enhance their skills. Additionally, Packt emphasizes personalized learning paths and provides analytics tools for educators to monitor student engagement and success, making it a valuable partner in academic settings.
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