Overview
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## Master R for Real-World Data Analysis
Become a data analyst and advance your career by mastering R, the leading programming language for statistical computing and data analysis. In this Track, you'll learn how to import, clean, manipulate, and visualize data using R's powerful packages and libraries, including dplyr, ggplot2, and the tidyverse. Through hands-on exercises with real-world datasets, you'll develop the essential skills that employers look for in data analysts.
## Build Your Data Analysis Toolkit
Progress from R basics to advanced data analysis techniques as you learn to:
* Clean, transform, and manipulate data using dplyr and tidyverse packages
* Create compelling data visualizations with ggplot2
* Perform exploratory data analysis to uncover patterns and trends
* Join and combine data from multiple sources
* Apply statistical methods for hypothesis testing and sampling
## Solve Real Business Problems with R
Apply your skills by working on projects that reflect the daily challenges faced by data analysts. Analyze customer behavior, identify market trends, and provide data-driven insights to stakeholders. By completing this Track, you'll have a portfolio of projects demonstrating your ability to tackle real-world data analysis tasks using R.
## Designed for Beginners and Experienced Analysts Alike
Whether you're new to programming or looking to upskill, this Track is designed to help you succeed. With no prior coding experience required, you'll start by learning the fundamentals of R programming before diving into more advanced data analysis techniques. Experienced analysts will benefit from the Track's focus on industry-standard tools and best practices.
## Why R for Data Analysis?
R has become the go-to language for data analysis due to its powerful statistical capabilities, extensive package ecosystem, and active community support. Its open-source nature and cross-platform compatibility make it accessible to everyone, while its flexibility allows analysts to tackle complex data challenges. As more organizations adopt R for their data analysis needs, mastering R skills can open up exciting career opportunities.
## Launch Your Data Analysis Career
Upon completing this Track, you'll be ready to:
* Apply for data analyst roles across industries
* Collaborate effectively with data science teams
* Make data-driven decisions to solve business problems
* Communicate insights through compelling visualizations and reports
* Continue learning and growing as a data professional
Syllabus
- Introduction to R
- Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
- Introduction to the Tidyverse
- Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.
- Data Manipulation with dplyr
- Build Tidyverse skills by learning how to transform and manipulate data with dplyr.
- Analyze the Popularity of Programming Languages
- Joining Data with dplyr
- Learn to combine data across multiple tables to answer more complex questions with dplyr.
- Introduction to Statistics in R
- Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data.
- Introduction to Data Visualization with ggplot2
- Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.
- Exploratory Data Analysis in R
- Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
- Sampling in R
- Master sampling to get more accurate statistics with less data.
- Hypothesis Testing in R
- Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
- Hypothesis Testing with Men's and Women's Soccer Matches
Taught by
Jonathan Cornelissen, Andrew Bray, David Robinson, James Chapman, Rick Scavetta, DataCamp Content Creator, Maggie Matsui, and Richie Cotton