Courses

  • 1 Topic

    Copy of Data on display: R plots with ggplot2

    This course will teach you how to harness the power of visualization in R to explore data and to present your findings to others. In addition to learning the mechanics of learning to write code for visualizations, you will also learn how to use the art of visualization to tell a story with your data. We will be focusing on learning how to use ggplot2, one of the the most popular R packages, to produce a variety of high quality visualizations.

    Topics include:

    • Building a plot in layers with ggplot2
    • Implementing the Grammar of Graphics in R
    • Visualization strategies for univariate, bivariate, and multivariate data
    • Histograms, boxplots, and kernel density plots for visualizing the distribution of continuous variables
    • Simple, stacked, and grouped barplots for visualizing the distribution of discrete variables
    • Scatterplots and linegraphs for visualizing the relationship between two continuous variables
    • Time series plots to visualize epidemic trends
    • Grouping and faceting plots to visualize relationships among three or more variables
    • Customizing plots with labels, color palettes, and themes

    During the beta release (November 28 to December 13), new lessons will be made public every week.

  • 1 Topic

    Data on display: R plots with ggplot2

    This course will teach you how to harness the power of visualization in R to explore data and to present your findings to others. In addition to learning the mechanics of learning to write code for visualizations, you will also learn how to use the art of visualization to tell a story with your data. We will be focusing on learning how to use ggplot2, one of the the most popular R packages, to produce a variety of high quality visualizations.

    Topics include:

    • Building a plot in layers with ggplot2
    • Implementing the Grammar of Graphics in R
    • Visualization strategies for univariate, bivariate, and multivariate data
    • Histograms, boxplots, and kernel density plots for visualizing the distribution of continuous variables
    • Simple, stacked, and grouped barplots for visualizing the distribution of discrete variables
    • Scatterplots and linegraphs for visualizing the relationship between two continuous variables
    • Time series plots to visualize epidemic trends
    • Grouping and faceting plots to visualize relationships among three or more variables
    • Customizing plots with labels, color palettes, and themes

    During the beta release (November 28 to December 13), new lessons will be made public every week.

  • 6 Topics

    Data Untangled: Wrangling with R (beta)

    Topics covered:
    • Selecting, filtering and mutating data frames
    • Grouping and summarizing
    • Joining multiple data frames
    • Reshaping data
     
  • 6 Topics

    Intro to EpiGraphHub (beta)

    This course aims to enable public health students and professionals to engage as advanced users with the EpiGraphHub platform, our data management, exploration and dashboarding platform. It requires minimal technical knowledge of coding or informatics.

    During this course, you will learn:

    • What the EpiGraphHub platform is, and what functionalities it offers to non-programmer users
    • What databases are available and how datasets are organised
    • How to browse available datasets
    • How to use the interactive drag & drop user interface to develop Exploratory analyses
    • How to create powerful data visualizations and interactive dashboards without writing code
    • How to import new data into the Hub from CSV files as well as Excel and Google spreadsheets
  • 28 Topics

    R for Busy People (Cohort-0)

    In preparation for the public launch of our flagship courses, we are excited to offer 12-weeks of free live training to a beta cohort of students. Over 3 months of instruction, you will learn how to:
    • Download, install and use R & RStudio
    • Work with R & Rmarkdown scripts and RStudio projects
    • Import and examine datasets in R
    • Wrangle data (by filtering, summarizing, transforming and joining)
    • Visualize data with the popular ggplot2 package
    • Publish reports and other outputs in a range of formats
    At the end, you will feel ready to tackle most basic and intermediate data analysis tasks with R, whether for your academic research, professional practice, or personal interest.
  • 7 Topics

    R foundations (beta)

    This course introduces the essential elements of the R programming language, providing a solid foundation for the more in-depth data analysis topics covered in subsequent courses.

    Topics include:

    • Installing R and RStudio
    • Importing data
    • Data structures and types
    • Basic data summarization and analysis with pre-built functions
    • Visualizing data with esquisse
    • Creating PDF, HTML and DOCX reports with rmarkdown
    • Getting help through online forums

    During the beta release, new lessons will be released periodically.