Lessons for Teaching Demonstrations
Last updated on 2024-07-24 | Edit this page
The list below shows lessons that have been reviewed for good and bad start points to use for a teaching demonstration. When selecting an episode for a teaching demonstration, trainees should review this list to ensure it is suitable.
As of 14 August 2023, trainees are allowed to choose the episode from which their 5-minute teaching demo will begin. However, still we recommend reviewing the full lesson during preparation, as this will help provide context for instruction and is also good preparation for teaching a complete workshop later on!
If a selected episode is very short and finishes in less than 5 minutes, it may be necessary to continue on to the next episode in that lesson to complete a 5 minute demonstration. It is not necessary to teach the full episode, or to cover any specific amount of content within the 5 minute period.
NB: If your preferred lesson is not on the list or includes only ineligible episodes, please choose a different lesson. If you believe you have a lesson or episode that should be eligible but is not on the list, please email us at instructor.training@carpentries.org.
Teaching Episodes with Dependencies
Many Carpentries lessons follow a narrative: an example that runs from episode to episode, with the same data, files, variables, etc reused and modified as new skills and concepts are taught to Learners. This means that the content of later episodes in a lesson is likely to depend on the steps that have taken place earlier in the lesson.
The Recommended Episodes column of the tables below provides a list of episodes that do not depend heavily on any of the preceding content in the lesson. If you choose to teach one of the episodes not in this list of recommendations, you should take care to ensure that you have everything set up as if the preceding parts of the lesson have already been taught before your teaching demonstration begins.
Ineligible Episodes for Teaching Demos
Some lessons include episodes that cannot be used for a teaching demonstrations, usually because they contain little or no opportunity for teaching by live demonstration. These episodes are listed in the Not Eligible for Demos column of the tables below.
Table of Contents
Use the links below to jump to the starting points information for a particular curriculum.
Data Carpentry: Ecology
Data Carpentry: Genomics
If you are an instructor in training and wish to use lessons from Data Carpentry’s Genomics curriculum for your teaching demo, please read these instructions to be sure you are prepared. You must follow these steps before your teaching demo, or you will be asked to reschedule.
Lesson | Recommended Episodes | Not Eligible for Demos | Notes |
---|---|---|---|
Project Organization and Management for Genomics | none | all episodes | This is a discussion-based lesson and provides no opportunities for live demonstration. It cannot be used for teaching demonstrations. |
Introduction to the Command Line | all episodes | none | If using Introducing
the Shell, begin with cd shell_data
|
Data Wrangling and Processing | * Assessing
Read Quality * Trimming and Filtering * Automating a Variant Calling Workflow |
none | The other episodes depend on actions taken earlier in the lesson -
consult Teaching Episodes with
Dependencies. If using Assessing Read Quality, begin with gunzip SRR2584863_1.fastq.gz
|
Introduction to Cloud Computing | * Logging
onto the Cloud * Fine tuning your Cloud Setup |
* Why
of Cloud Computing * Which Cloud for my Data? |
|
Data Analysis and Visualization in R | none | all episodes | This lesson is not yet stable and cannot be used for teaching demonstrations. |
Data Carpentry: Social Sciences
Lesson | Recommended Episodes | Not Eligible for Demos | Notes |
---|---|---|---|
Data Organization in Spreadsheets | * Dates
as Data * Quality Assurance |
* Introduction * Formatting Data Tables in Spreadsheets * Formatting problems * Exporting data |
|
Data Cleaning with OpenRefine | Working with OpenRefine | * Introduction | The other episodes depend on actions taken earlier in the lesson - consult Teaching Episodes with Dependencies. |
Data Analysis and Visualization with R | * Introduction
to R * Starting with Data * Data Wrangling with dplyr * Data Wrangling with tidyr * Getting Started with R Markdown * Processing JSON Data |
* Before We Start | Data Visualization with ggplot2 depends on action taken earlier in the lesson - consult Teaching Episodes with Dependencies. |
Data Carpentry: Geospatial
Lesson | Recommended Episodes | Not Eligible for Demos | Notes |
---|---|---|---|
Introduction to Geospatial Concepts | none | all episodes | This is a discussion-based lesson and provides no opportunities for live demonstration. It cannot be used for teaching demonstrations. |
Introduction to R for Geospatial Data | all episodes | none | |
Introduction to Raster and Vector Data with R | * Intro
to Raster Data in R * Reproject Raster Data * Work with Multi-Band Rasters * Open and Plot Vector Layers * Handling Spatial Projection & CRS * Convert from a .csv to a Vector Layer * Raster Time Series Data |
none | The other episodes depend on actions taken earlier in the lesson -
consult Teaching Episodes with
Dependencies. You may need to allow yourself extra time to set up your environment to demo this lesson. |
Data Carpentry: Astronomy
Lesson | Recommended Episodes | Not Eligible for Demos | Notes |
---|---|---|---|
Foundations of Astronomical Data Science | * Basic
Queries * Coordinate Transformations |
none | The other episodes depend on actions taken earlier in the lesson -
consult Teaching Episodes with
Dependencies. If using Basic Queries, skip the episode introduction, Query Language, and Using Jupyter sections, and begin with Connecting to Gaia ( from astroquery.gaia import Gaia ) |
Data Carpentry: Image Processing
Lesson | Recommended Episodes | Not Eligible for Demos | Notes |
---|---|---|---|
Image Processing with Python | * Working
with skimage * Drawing and Bitwise Operations * Creating Histograms * Thresholding |
* Introduction * Blurring Images * Capstone Challenge |
If using Image
Basics, start from Working
with Pixels. If using Connected Component Analysis, start from the Connected Component Analysis section. This lesson is designed to be taught with a JupyterLab environment - check the lesson’s Instructor Notes for further guidance. |
Library Carpentry
Lesson | Recommended Episodes | Not Eligible for Demos | Notes |
---|---|---|---|
Library Carpentry: The Unix Shell | * Navigating
the filesystem * Working with files and directories * Automating the tedious with loops * Counting and mining with the shell * Working with free text |
* What is the shell? | |
Library Carpentry: OpenRefine | * Importing data into OpenRefine | * Introduction to OpenRefine | The other episodes depend on actions taken earlier in the lesson - consult Teaching Episodes with Dependencies. |
Library Carpentry: Introduction to Working with Data (Regular Expressions) | none | all episodes | This is a discussion-based lesson and provides no opportunities for live demonstration. It cannot be used for teaching demonstrations. |
Library Carpentry: Introduction to Git | * Getting started with Git | * What is Git/GitHub? | The other episodes depend on actions taken earlier in the lesson - consult Teaching Episodes with Dependencies. |
Library Carpentry: SQL | * Selecting
and Sorting Data * Filtering * Ordering and Commenting * Aggregating and Calculating Values * Joins and aliases * Saving queries * Creating tables and modifying data |
*Introduction
to SQL * Database design * Other database tools * Extra-challenges * Good style |
These episodes do not have opportunities for live demonstration |
Library Carpentry: Introduction to Tidy Data | none | all episodes | This lesson is not yet stable and cannot be used for teaching demonstrations. |
Library Carpentry: Introduction to Python | none | all episodes | This lesson is not yet stable and cannot be used for teaching demonstrations. |
Library Carpentry: Introduction to Data for Archivists | none | all episodes | This lesson is not yet stable and cannot be used for teaching demonstrations. |
Library Carpentry: Introduction to R | none | all episodes | This lesson is not yet stable and cannot be used for teaching demonstrations. |
Library Carpentry: Introduction to MarcEdit | none | all episodes | This lesson is not yet stable and cannot be used for teaching demonstrations. |
Library Carpentry: Introduction to AI for GLAM | none | all episodes | This lesson is not yet stable and cannot be used for teaching demonstrations. |
Software Carpentry
Lecciones en español
Enseñanza de episodios con dependencias
Muchas lecciones en Carpentries siguen una narrativa común: Un mismo ejemplo que va de episodio en episodio, con datos, archivos, variables, etc. que son reutilizados y modificados a medida que nuevas habilidades y conceptos son enseñados a los alumnos. Esto significa que el contenido de los episodios dependerá probablemente de los pasos que se hayan dado en episodios anteriores de una misma lección.
La columna Episodios Recomendados en la tabla siguiente proporciona una lista de episodios que no dependen en gran medida de ninguno de los contenidos anteriores de la lección. Si decide enseñar uno de los episodios que no figuran en esta lista de recomendaciones, deberá asegurarse de que todo está preparado como si las partes anteriores de la lección ya se hubieran enseñado antes de comenzar su demostración didáctica.
Episodios no aptos para la demostración didáctica
Algunas lecciones incluyen episodios que no pueden ser utilizados para una demostración didáctica, normalmente porque contienen poca o ninguna oportunidad para la enseñanza mediante demostraciones en vivo. Estos episodios se enumeran en la columna No elegible para demostraciones en la tabla siguiente.
Lección | Episodios Recomendados | No elegible para demostraciones | Notas |
---|---|---|---|
La Terminal de Unix | cualquier otro episodio | * Introducción a la Terminal | |
Control de versiones con Git | * Configurando
Git * Creando un repositorio * Rastreando Cambios |
* Control Automatizado de Versiones | Los episodios posteriores dependen de las acciones realizadas anteriormente en la lección (consulte Enseñanza de episodios con dependencias). |
R para Análisis Científicos Reproducibles | cualquier otro episodio | * Escribiendo buen software | |
Análisis y visualización de datos usando Python | * Breve
introducción a la Programación en Python * Comenzando con datos * Indexación, segmentación y creación de subconjuntos * Tipos de datos y formatos * Combinando DataFrames con Pandas * Flujos de trabajo y automatización |
* Antes de comenzar | Los episodios posteriores dependen de las acciones realizadas anteriormente en la lección (consulte Enseñanza de episodios con dependencias). |