Constant development is one of our paradigms. At Hypermynds we use cutting-edge
technology which is the result of thorough research.
With the Hypermynds Academy we want to share our knowledge with several
courses and modules, from the basics of data science to the most advanced
topics, all developed within the R framework.
You can find courses that cover specific areas or general ones, we offer
tailored on-site training for large and small companies.
Our trainers will guide you through the learning process by sharing their
expertise on both theory and practice: we only teach what we have solid
experience on.
R for Excel users
Basic
Overview
This course will introduce you to the R world, showing all its
potential.
The objective of the course is to switch paradigm from spreadsheet
to the more powerful R. You will learn how to quickly and
effectively import data and perform standard
data operations.
There will be case studies and examples of how you can improve your
productivity and get faster results by using R instead of Excel.
Outline
Data types: how the data is stored in the R environment
Data entry: how to import and export data using R
Data cleaning: how to check and correct your datasets
Data analysis: how to quickly summarise your data with meaningful statistics
Data visualization: how to produce effective graphs and charts from your data
Case studies: when and how R is better than Excel (and when it is not)
Prerequisites
Intermediate knowledge of Excel.
Basic knowledge of statistics.
Data visualization and reporting with R
Basic
Overview
This course focuses on producing automated reports with R.
With Rmarkdown you will learn how to turn your analyses into high
quality documents, reports and presentations.
The ultimate goal of the course is to teach a user how to set up
reproducible reports that are fully automated and save a lot of time
on repetitive tasks.
Outline
Review of the basic data analysis concepts with R.
Introducing highcharter for interactive charts.
Introducing Rmarkdown for reporting.
Case study: automate the process of data loading and
producing a monthly report.
Prerequisites
Basic knowledge of R.
Packages
dplyr, tidyr, highcharter, rmarkdown
Data analysis with R and the tidyverse
Intermediate
Overview
This course teaches you the foundation of the tidyverse:
a coherent system of R packages for data manipulation, exploration and
visualization.
You will learn how to import, tidy, transform and report your
data in a more efficient way with the clear workflow that made the tidyverse
a golden standard in the R community.
Outline
Tibbles: what are the advantages of using this structure
over more traditional data frames.
Dplyr: learn data operations such as filtering, grouping
and joining tables.
Date/time operations with lubridate.
Make elegant plots and reports with ggplot.
Prerequisites
Basic knowledge of R.
Basic knowledge of data analysis.
Packages
dplyr, tibble, tidyr, lubridate
Geospatial data with R
Intermediate
Overview
This course presents R as a GIS (geographic information system).
You will learn how to handle geographic data and how to produce
elegant maps, with customizable icons and interactive content.
Outline
The structure of geographic data in R.
How to customize your maps with the leaflet package for interactive
geographic data.
Styling and editing your maps with icons and plugins.
Prerequisites
Basic knowledge of R.
Previous experience with the tidyverse (dplyr & tidyr)
Packages
sf, dplyr, leaflet, leaflet.extras
Interactive dashboards with Shiny
Advanced
Overview
In this course you will be introduced to Shiny: an R extension
for creating cutting-edge interactive web applications.
You will learn the basic concept of a Shiny infrastructure and you will
be guided step-by-step in the development of an interactive dashboard
starting from raw data.
Outline
Basic concepts: user interface and server in R Shiny.
Introduction to HTML: you will learn the basics for styling
your user interface.
Reactive programming: how to create functions that handle some
content customizable by the user, or by other functions.
Case Study: build an interactive dashboard with interactive data
tables and charts, starting from a raw dataset.
Prerequisites
Intermediate knowledge of R
(Preferable) basic understanding of HTML.
Packages
shiny, HTML, shinydashboard
Full stack development with R
Advanced
Overview
This course will guide you through all the necessary steps for
the deployment of an efficient and professional Shiny application
with object oriented programming.
Outline
R6 classes: you will be introduced to object oriented
programming in R, with a focus on how to take advantage of
specific features for Shiny app development purposes.
CRUD dynamics: you will learn how to set up a data
structure that will serve as the back-end of your final
application using standard database engines. You will
encapsulate the structure and the CRUD (create, read, update,
delete) within a single R6 class object.
Shiny App: you will add methods to your existing
object that will be used as front-end. The application will be
connected to the database and you will be able to create an
interactive dashboard that gives the user total freedom on the
data, allowing multiple operations such as data-entry,
filtering, update and data removal.
Reproducibility: you will understand how this seemingly
complex structure is really powerful for building full-stack
applications and how easy it will be to reutilize your code for
setting up different applications that manipulate data.
UI Styling: you will use basic HTML/CSS to prettify and
improve the user experience.
Prerequisites
Basic understanding of database structures.
Basic Shiny knowledge.
Intermediate R knowledge.
(Preferable) previous experience with the tidyverse.