Small/smol Nextflow - testing out ideas only

docs/index.md

@@ -64,6 +64,18 @@ These are foundational, domain-agnostic courses intended for those who are compl
 
     [Start the Nextflow Run training :material-arrow-right:](nextflow_run/index.md){ .md-button .md-button--primary }
 
+!!! exercise "Small Nextflow"
+
+    !!! tip inline end ""
+
+        :material-cat:{.nextflow-primary} Build a complete workflow from scratch.
+
+    This is a hands-on workshop where you build a real-world image classification workflow from the ground up. You'll learn Nextflow fundamentals by creating channels, defining processes, working with operators, and making your workflow reproducible and portable. Perfect for learners who prefer building something concrete while learning core concepts.
+
+    The course is calibrated to take a half day to cover in group trainings.
+
+    [Start the Small Nextflow workshop :material-arrow-right:](small_nextflow/index.md){ .md-button .md-button--primary }
+
 !!! exercise "Hello nf-core"
 
     !!! tip inline end ""

docs/small_nextflow/00_orientation.md

@@ -0,0 +1,75 @@
+# Orientation
+
+This orientation assumes you have already opened the training environment by clicking on the "Open in GitHub Codespaces" button.
+If not, please do so now, ideally in a second browser window or tab so you can refer back to these instructions.
+
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/nextflow-io/training/tree/smol-nextflow?quickstart=1&ref=master)
+
+## GitHub Codespaces
+
+The GitHub Codespaces environment contains all the software, code and data necessary to work through this training course, so you don't need to install anything yourself.
+However, you do need a (free) GitHub account to log in, and you should take a few minutes to familiarize yourself with the interface.
+
+If you have not yet done so, please go through the [Environment Setup](../../envsetup/) mini-course before going any further.
+
+## Working directory
+
+Throughout this training course, we'll be working in the `small_nextflow/` directory.
+
+Change directory now by running this command in the terminal:
+
+```bash
+cd small_nextflow/
+```
+
+!!!tip
+
+    If for whatever reason you move out of this directory, you can always use the full path to return to it, assuming you're running this within the GitHub Codespaces training environment:
+
+    ```bash
+    cd /workspaces/training/small_nextflow
+    ```
+
+Now let's have a look at the contents of this directory.
+
+## Materials provided
+
+You can explore the contents of this directory by using the file explorer on the left-hand side of the training workspace.
+Alternatively, you can use the `ls` command.
+
+Here we list the contents of the directory:
+
+```bash
+ls -la
+```
+
+If you run this inside `small_nextflow`, you should see a minimal directory structure:
+
+```console title="Directory contents"
+.
+├── .stuff/
+    ├── cat_me.sh
+    ├── classify.py
+    └── pyproject.toml
+```
+
+**Here's a summary of what you should know to get started:**
+
+- **The `.stuff/` directory** contains helper scripts and configuration files we'll use throughout the workshop.
+  You can think of this as a toolbox we'll pull from as we build our workflow.
+
+- **The `cat_me.sh` script** fetches random cat images from an API for our workflow to process.
+
+- **The `classify.py` script** is a Python program that uses machine learning to classify images.
+
+- **The `pyproject.toml` file** describes the Python dependencies needed for the classification script.
+
+Throughout this workshop, we'll start with this minimal setup and progressively build a complete image classification workflow.
+
+Let's get started by creating a fresh, empty `main.nf`:
+
+```bash
+code main.nf
+```
+
+**Now, to begin the course, click on the arrow in the bottom right corner of this page.**