Incubator on The Carpentries

End of Support for Our Previous Lesson Infrastructure

Wed, 25 Feb 2026 00:00:00 +0000

Following the January 2025 announcement that The Carpentries would sunset support for our previous lesson infrastructure, styles, at the end of last year, the Curriculum Team has been archiving repositories that had not migrated to The Carpentries Workbench over the last few weeks.

All of our official lessons had been expertly transitioned by Zhian Kamvar, our former Lesson Infrastructure Developer and architect of the Workbench, during the initial rollout of the new tooling in 2023. By the beginning of 2025, the majority of the community’s lessons in The Carpentries Incubator and Carpentries Lab had either been created with the Workbench or already been converted to use it. This included many that were migrated to the Workbench during a hackathon session at CarpentryConnect Heidelberg 2024, led by Aleksandra Nenadic and Matthew Bluteau.

Incubator Lesson Spotlight: Interactive Data Visualizations in Python

Wed, 27 Apr 2022 00:00:00 +0000

The first virtual CarpentryConnect South Africa 2021 took place from 6 to 17 September. The event included 2 Carpentries workshops, 1 Carpentries instructor training event, 2 networking events, 1 learning session and 1 opening address.

The main goal of CarpentryConnect South Africa 2021 was to build capacity for workshops through instructor training and bring together newer and more experienced community members to share knowledge, network, develop new skills, and develop strategies for building strong local communities around digital and computational literacy in Africa.

Incubator Lesson Spotlight: Intermediate Research Software Development in Python

Wed, 02 Mar 2022 00:00:00 +0000

The Incubator Lesson Spotlight highlights a lesson under development by our community in The Carpentries Incubator. In this edition, we look at the progress being made on the {{page.lesson_title}} lesson, and hear from the authors about how The Carpentries community can get involved with the ongoing development of this lesson.

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/python-intermediate-development/
Lesson Repository: https://github.com/carpentries-incubator/python-intermediate-development

Learning Objectives

After this course, learners should be able to:

Set up and use a suitable development environment together with popular source code management infrastructure to develop software collaboratively
Use a test framework to automate the verification of correct behaviour of code, and employ parameterisation and continuous integration to scale and further automate your testing
Design robust, extensible software through the application of suitable programming paradigms and design techniques
Use a critical, reflective mindset to prepare and release your software for reuse by others
Manage software improvement from feedback through agile techniques

Target Audience

A typical learner is someone who is working in academic research and, needing to write some code, has gained basic software development skills either by self-learning or attending, e.g., a novice Software Carpentry Python course. They have been applying those skills in their domain of work by writing code for some time, e.g. half a year or more. However, their software development-related projects are now becoming larger and are involving more stakeholders, and they now need more intermediate software engineering skills to help them design more robust software code, automate the process of testing and verifying its correctness and support collaborations with others.

Incubator Lesson Spotlight: Building Websites with Jekyll & GitHub Pages

Tue, 11 Jan 2022 00:00:00 +0000

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/jekyll-pages-novice/
Lesson Repository: https://github.com/carpentries-incubator/jekyll-pages-novice

Learning Objectives

After this lesson, learners should be able to:

create formatted page content with Markdown
configure their project to build and serve pages on GitHub
build a coherent site with multiple pages using the Jekyll framework
customise the layout and style of the pages on their site

Target Audience

This lesson guides learners through making websites using Jekyll in a web hosting service GitHub Pages. Anyone comfortable interacting with websites in a web browser and willing to learn how to produce website. Basic understanding of HTML and/or Markdown as webpage authoring languages is welcome but not a must.

Incubator Lesson Spotlight: Interactive Data Visualizations in Python

Tue, 21 Sep 2021 00:00:00 +0000

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/python-interactive-data-visualizations/
Lesson Repository: https://github.com/carpentries-incubator/python-interactive-data-visualizations

Learning Objectives

Learn how to wrangle data into a tidy format using the pandas library.
Learn how to create some basic visualizations using the Plotly Express library.
Learn how to create a web app using the Streamlit library for sharing the visualizations, as well as interacting with the data and visualizations via widgets.

Target Audience

This workshop is appropriate for learners who have recently completed the “Plotting and Programming in Python” lesson (or have some experience with Python and pandas), and is targeted specifically to those who want to learn more about creating data visualizations and building interactive dashboards. The lesson can be taught in 1 hour (if you skip the exercises and include Episode 1 in the prep) or up to 2 hours (if you include time for students to work through all the exercises and include Episode 1 in the workshop time).

Incubator Lesson Spotlight: Programming with Julia

Wed, 04 Aug 2021 00:00:00 +0000

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/julia-novice/
Lesson Repository: https://github.com/carpentries-incubator/julia-novice

Learning Objectives

using the Julia REPL
get comfortable with the package manager and environments
learn syntax for common tasks (types, control flow, functions & methods, modules)
finding, using and creating packages
writing tests

Target Audience

People with some programming experience that are new to Julia. Particularly people doing scientific computing.

Incubator Lesson Spotlight: Analysis and Interpretation of Bulk RNA-Seq Data using Bioconductor

Tue, 13 Jul 2021 00:00:00 +0000

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/bioc-rnaseq
Lesson Repository: https://github.com/carpentries-incubator/bioc-rnaseq

Learning Objectives

After following this lesson, learners will be able to:

choose an appropriate design for a bulk RNA Sequencing experiment.
import and annotate quantified RNA-Seq data in R.
assess the quality of experimental results represented as a gene expression matrix.
run a standard differential expression analysis and interpret the output.
execute a gene set analysis.

Target Audience

This lesson is aimed at researchers who are already aware of what Bioconductor is and how it can benefit their data analysis. They are comfortable with basic operations in R, such as creating numeric, character vector, and data frame variables, installing and loading packages from CRAN and Bioconductor, and visualising data in common formats such as bar and scatter plots. These researchers want to learn how to use R and Bioconductor to explore and analyse data produced in bulk RNA sequencing experiments, and visualise and interpret the results of these analyses.

Reflecting on our first Alpha Test of the Lesson Infrastructure Redesign

Tue, 06 Jul 2021 00:00:00 +0000

Introduction

This is an ongoing series of blog posts about the next iteration of the [Lesson Infrastructure]({{ site.url }}/posts-by-tags/#lesson-infrastructure). Find more about our Design Principles and our Path to the Design for the Lesson Website

As our community has grown in the past few years, it has become evident that our current lesson infrastructure—where implementing updates involves complex manual steps—does not scale well. It was also evident that the lesson development toolchain was intimidating enough that it was—in and of itself—a barrier to contribution. When this infrastructure was created back in 2016, we had only a few lessons that were maintained by a small group of maintainers who were able to install the toolchain and render them locally. We now have more than 100 official and community-developed lessons combined. Based on the feedback from our much larger maintainer community, it is clear that many find it challenging to keep the infrastructure up-to-date on their own machines.

Incubator Lesson Spotlight: Foundational Computer Skills

Wed, 30 Jun 2021 00:00:00 +0000

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/foundational-computer-skills
Lesson Repository: https://github.com/carpentries-incubator/foundational-computer-skills

Learning Objectives

To recognize different extensions and format of the data files and software packages
To identify appropriate software suitable to learners’ environment
To be able to download data, place in appropriate location, extract, and load data
To be able to download, install, configure, and test software

Target Audience

Learners preparing for a workshop
Instructors and helpers helping with pre-workshop setup

Lesson Progress

The lesson is in the initial stages of development (pre-alpha).

Incubator Lesson Spotlight: Bash and R for Metagenomics

Mon, 17 May 2021 00:00:00 +0000

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/metagenomics/
Lesson Repository: https://github.com/carpentries-incubator/metagenomics

Learning Objectives

Acknowledge the importance of well-organized bioinformatics projects and apply this sense of tidiness to metagenomics data.
Learn and implement the guidelines for reproducible metagenomics projects.
Understand and apply the basics for Bash and R programming languages.
Use of Bash and R programming languages to assess and manipulate metagenomics data.
Learn and use the steps and tools for a complete analysis of shotgun and 16S metagenomics data.

Target Audience

Genomics and metagenomics enthusiasts; newcomers to the bioinformatics world; biological science undergraduate, postgraduate students and researchers. We do not assume previous knowledge of Bash, R or metagenomics for the lesson.

Incubator Lesson Spotlight: Python for Business

Tue, 20 Apr 2021 00:00:00 +0000

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/python-business/
Lesson Repository: https://github.com/carpentries-incubator/python-business

Learning Objectives

teach data processing skills that are automated, repeatable, and testable
apply Python as a replacement for spreadsheet-based analysis

Target Audience

Python for Business is a software skills training programme aimed at business students. It helps business students learn about basics of programming and how to perform Excel-like tasks with Python.

Incubator Lesson Spotlight: Introduction to Open Data Science with R

Wed, 24 Mar 2021 00:00:00 +0000

Lesson Profile

Title: {{page.lesson_title}} Lesson Pages: https://carpentries-incubator.github.io/open-science-with-r/ Lesson Repository: https://github.com/carpentries-incubator/open-science-with-r

Learning Objectives

After this lesson, learners should.. Know best practices in data analysis with R: tidy format, transformation, filtering, etc. Know how to increase scientific reproducibility and openness by coupling R with version control (git). Be able to create literate programming reports using R Markdown.

Call for Pilot Workshops: Neuroimaging Lessons

Wed, 10 Mar 2021 00:00:00 +0000

An important step in the process of developing a new lesson is the moment when material is taught for the first time by someone other than the original author(s). In our description of the lesson life cycle we refer to these events as beta pilot workshops. After teaching the new lesson material, Instructors provide feedback to the lesson developer(s) to enable the lesson to be further polished in final preparation for an official release.

Incubator Lesson Spotlight - Reproducible Computational Environments Using Containers: Introduction to Docker

Tue, 23 Feb 2021 00:00:00 +0000

The Incubator Lesson Spotlight highlights a lesson under development by our community in The Carpentries Incubator. In this first feature of the series, we look at the progress being made on the {{page.lesson_title}} lesson, and hear from the authors about how The Carpentries community can get involved with the ongoing development of this lesson.

Lesson Profile

Title: {{page.lesson_title}}
Lesson Pages: https://carpentries-incubator.github.io/docker-introduction/
Lesson Repository: https://github.com/carpentries-incubator/docker-introduction

Learning Objectives

After this lesson, learners should..

Know what containers are and how they can be useful
Know how to find and use containers created by someone else
Know how to create and share your own containers
Understand how to take the next step in your use of containers

Target Audience

Our target audience is researchers who want to learn how to use containers to help manage computational environments and enhance the reproducibility of their research results. Learners should have some experience with the Unix shell, e.g., from having completed the Software Carpentry lesson, “The Unix Shell”.

Alpha testing a Jekyll Pages lesson

Tue, 19 Jan 2021 00:00:00 +0000

In the past several months, we have been developing a lesson, Building Websites with Jekyll and GitHub Pages, in The Carpentries Incubator. In November 2020, we taught this material for the first time in two mini-workshops hosted by UW-Madison.

The first time a lesson is taught is always an important step in its development. It is a chance to really assess how well the lesson objectives and material fit the target audience.

It is also usually the first time exercises have been tested by learners, and can expose weaknesses in the material that are difficult to spot from our perspective as a lesson author. In the life cycle of a lesson, The Carpentries refer to these initial trial runs undertaken by lesson authors as alpha pilots.

Call for Pilot Workshops: Introduction to Conda for (Data) Scientists

Thu, 29 Oct 2020 00:00:00 +0000

Design principles for the next iteration of The Carpentries lesson template

Mon, 10 Aug 2020 00:00:00 +0000

This blog post introduces twelve design principles that will guide the development of the next version of The Carpentries lesson template. First, we provide some background and definitions. If you are more interested in the principles themselves, you can skip forward to the Design Principles section.

Background

In The Carpentries’ history (including Data Carpentry, Library Carpentry, and Software Carpentry), we have learned a lot about lesson templates. We have had two main versions of the template that relied on GitHub Pages. As the community grows, we are adding more lessons through [our community-developed lessons]({{ site.url }}/community-lessons/) (The Carpentries Incubator and The Carpentries Lab) every week; and we are starting to see the limitations of our current workflow. Given changes in the tools and infrastructure, we are envisioning the next iteration of the lesson template.

Teaching a New Geospatial Python Lesson

Tue, 10 Mar 2020 00:00:00 +0000

On February 6-7, 2020, the NASA DEVELOP program at Jet Propulsion Laboratory(JPL) hosted the initial run of Introduction to Geospatial Raster and Vector Data with Python, a Carpentries incubator lesson. This lesson was imagined as a Python complement to Introduction to Geospatial Raster and Vector Data with R, an existing Data Carpentry lesson.

Kunal Marwaha and Ryan Avery, the lesson authors, served as instructors. We had 8 attendees; the small learner size helped us work through hiccups in the new material. Most attendees were recent graduates in a field related to remote sensing or geographic information systems. We had a range of previous experience level, including folks who use Python daily, weekly, and never.