Brief Introduction
You will...Course Summary
Learn how to use R for data analysis and visualization in this comprehensive course from Udacity. Gain skills in statistical analysis, data wrangling, and data visualization.Key Learning Points
- Learn how to use R for data analysis and visualization
- Gain skills in statistical analysis, data wrangling, and data visualization
- Understand R programming concepts and best practices
Related Topics for further study
Learning Outcomes
- Understand R programming concepts and best practices
- Perform statistical analysis using R
- Create visualizations to communicate insights
Prerequisites or good to have knowledge before taking this course
- Basic programming knowledge
- Familiarity with statistics
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Project-based
Similar Courses
- Data Analysis with Python
- Data Wrangling with MongoDB
- Data Visualization with D3.js
Related Education Paths
Notable People in This Field
- Hadley Wickham
- Mara Averick
Related Books
Description
Data is everywhere and so much of it is unexplored. Learn how to investigate and summarize data sets using R and eventually create your own analysis.Requirements
- A background in statistics is helpful but not required. Consider taking Intro to Descriptive Statistics prior to taking this course. Relevant topics include: Mean, median, mode Normal, uniform, and skewed distributions Histograms and box plots Familiarity with the following CS and Math topics will help students: Variable assignment Comparison and logical operators (
- ,
- =, ==, &, | ) If else statements Square roots, logarithms, and exponentials See the Technology Requirements for using Udacity.
Knowledge
- Instructor videosLearn by doing exercisesTaught by industry professionals
Outline
- lesson 1 What is EDA? Start by learn about what exploratory data analysis (EDA) is and why it is important. lesson 2 R Basics EDA which comes before formal hypothesis testing and modeling makes use of visual methods to analyze and summarize data sets. R will be our tool for generating those visuals and conducting analyses. We will install RStudio and packages learn the layout and basic commands of R practice writing basic R scripts and inspect data sets. lesson 3 Explore One Variable Perform EDA to understand the distribution of a variable and to check for anomalies and outliers. Learn how to quantify and visualize individual variables within a data set to make sense of a pseudo-data set of Facebook users. Create histograms and boxplots transform variables and examine tradeoffs in visualizations. lesson 4 Explore Two Variables DA allows us to identify the most important variables and relationships within a data set before building predictive models. Learn techniques for exploring the relationship between any two variables in a data set. Create scatter plots calculate correlations and investigate conditional means. lesson 5 Explore Many Variables Learn powerful methods and visualizations for examining relationships among multiple variables. Reshape data frames and how to use aesthetics like color and shape to uncover more information Continue to build intuition around the Facebook data set and explore some new data sets as well. lesson 6 Diamonds and Price Predictions Investigate the diamonds data set alongside Facebook Data Scientist Solomon Messing. See how predictive modeling can allow us to determine a good price for a diamond. As a final project you will create your own exploratory data analysis on a data set of your choice.
Summary of User Reviews
The Data Analysis with R course on Udacity has received high praise from many users for its comprehensive curriculum and engaging instructors. One key aspect that users found particularly valuable was the hands-on approach to learning that allows them to apply what they've learned in real-world scenarios.Pros from User Reviews
- Comprehensive curriculum
- Engaging instructors
- Hands-on approach to learning
- Real-world scenarios
Cons from User Reviews
- Some users found the course to be too basic
- A few users experienced technical issues with the platform
- The course may require more time commitment than expected
- Some users felt that the course could benefit from more interactive elements
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