Delve further into the Tidyverse by learning to transform and manipulate data with dplyr.
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Transform almost any dataset into a tidy format to make analysis easier.
Analyze text data in R using the tidy framework.
The xts and zoo packages make the task of managing and manipulating ordered observations fast and mistake free.
Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.
Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.
This course will show you how to combine and merge datasets with data.table.
Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.
Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.
Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.
Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.
Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.
Apply your importing and data cleaning skills to real-world soccer data.
Discover the top tools Kaggle participants use for data science and machine learning.
Use tree-based machine learning methods to identify the characteristics of legendary Pokémon.
Load, clean, and explore Super Bowl data in the age of soaring ad costs and flashy halftime shows.
Analyze health survey data to determine how BMI is associated with physical activity and smoking.
Apply hierarchical and mixed-effect models to analyze Maryland crime rates.
Use your logistic regression skills to protect people from becoming zombies!
Predict the impact of climate change on bird distributions using spatial data and machine learning.
Use cluster analysis to glean insights into cryptocurrency gambling behavior.
Apply unsupervised learning techniques to help plan an education program in Argentina.
Use data science to catch criminals, plus find new ways to volunteer personal time for social good.
Explore the salary potential of college majors with a k-means cluster analysis.
Analyze admissions data from UC Berkeley and find out if the university was biased against women.
Analyze the dialog and IMDB ratings of 287 South Park episodes. Warning: contains explicit language.
Experiment with clustering algorithms to help doctors inform treatment for heart disease patients.
Explore acoustic backscatter data to find fish in the U.S. Atlantic Ocean.
Write functions to forecast time series of food prices in Rwanda.
Apply text mining to Donald Trump's tweets to confirm if he writes the (angrier) Android half.
Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.
Apply your skills from "Working with Dates and Times in R" to breathalyzer data from Ames, Iowa.
Create and explore interactive maps using Leaflet to determine where to open the next Chipotle.
How can we find a good strategy for reducing traffic-related deaths?
Examine the relationship between heart rate and heart disease using multiple logistic regression.
Examine the network of connections among local health departments in the United States.
Analyze the relative popularity of programming languages over time based on Stack Overflow data.
Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?
Flex your data manipulation muscles on breath alcohol test data from Ames, Iowa, USA.
Apply your knowledge of data types and categorical data to prepare a big dataset for modeling!
Reanalyze the data behind one of the most important discoveries of modern medicine: handwashing.
Compare life expectancy across countries and genders with ggplot2.
Apply your importing and cleaning data and data manipulation skills to explore New York City Airbnb data.
Analyze data from the hit mobile game, Candy Crush Saga.
Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.
Analyze the relative popularity of programming languages over time based on Stack Overflow data.
Write functions to forecast time series of food prices in Rwanda.