Jupyter Notebooks.
No Servers Required.
A full notebook experience running entirely in the browser — NumPy, Pandas, Matplotlib, Plotly, Panel, interactive terminal, and inline plots. Every learner gets their own kernel instantly.
Built on Pyodide (Python compiled to WebAssembly). No JupyterHub. No containers. No IT tickets. Notebooks live directly inside the curriculum alongside reading, exercises, and AI tutoring.
Notebooks Live Inside the Textbook
Code cells, rich narrative, terminal output, inline plots, file uploads, and interactive widgets — all on a single page alongside the curriculum. No separate app, no context-switching.
Teach. Don't Troubleshoot Infrastructure.
Eliminate everything between your curriculum and your learners. No servers to provision, no environments to configure, no submission pipelines to wrangle.
Zero Infrastructure
No JupyterHub, no Docker, no cloud compute. The Python kernel runs in each learner's browser natively.
See Every Learner's Work
Select any learner and see their exact notebook state — code, outputs, execution. No collecting files.
Auto-Grading Built In
Unit tests per cell with inline pass/fail. Results flow into the gradebook — no nbgrader required.
Progress Analytics
Track cell execution, attempt counts, and time spent. Spot struggling learners early.
Part of the Curriculum
Notebooks live inline with reading, exercises, and AI tutoring — not as standalone .ipynb files.
Secure by Default
Code runs in a browser sandbox — no OS access, no server to compromise, no cross-learner risk.
A Real Notebook Experience.
Nothing to Install.
Run code cells, see plots inline, interact with a terminal — from any Chromebook, tablet, or school PC.
Real Terminal, Streaming Live
Output streams in real time. input() works interactively, just like a local terminal.
- ✓ Streaming output as code runs
- ✓ Interactive prompts — learners type responses directly
- ✓ Stop button halts runaway code instantly
name = input(f"Student {'{'}i+1{'}'}: ")
print(f"Hello, {'{'}name{'}'}!")
Hello, Alice!
>>> Student 2: _
See Exactly What Changed
Line-by-line diff of edits against the starter code. Teachers see the same view.
- ✓ One-click reset to the original content
- ✓ Edits auto-saved — no manual submit workflow
- ✓ IPython magics (%pip, %timeit, %who) work out of the box
See Any Learner's Work Instantly
Select a learner and see their exact notebook — code, outputs, execution state. No file collection.
- ✓ Live progress — see who completed which cells
- ✓ Built-in grading with rubric support
- ✓ Role-aware UI: learners edit, teachers grade
Adjusted Gross receipts in millions of dollars. Use np.round to retain only two decimal places.
# millions = top.select(0).with_columns(...)
# millions
Select a learner from the dropdown to view their work.
Load Data from Anywhere
Upload local files, pull from Google Drive, an HTTP Url, or use pre-loaded curriculum data into your data science library.
- ✓ Upload files from the local machine — CSV, JSON, and more
- ✓ Google Drive picker with OAuth loads Sheets and CSVs directly
- ✓ Curriculum data files pre-loaded in a virtual file system
# Securely load CSV and Spreadsheet from Google Drive
df = pd.read_csv("https://drive.google.com/file/d/1.../view")
df.head()
| name | score | grade | |
|---|---|---|---|
| 0 | Alice | 92 | A |
| 1 | Brian | 78 | B+ |
| 2 | Carmen | 85 | A- |
| 3 | David | 64 | C |
Build Interactive Apps in the Notebook
ipywidgets, Panel, and LLM APIs — all rendering live inline.
- ✓ Full ipywidgets support — sliders, dropdowns, buttons with real-time callbacks
- ✓ Panel dashboards and chatbots render live in output cells
- ✓ Intro to Generative AI course included — chatbots, prompt engineering, RAG
reply = get_completion(msg.value)
log.object += f"<b>You:</b> {'{'}msg.value{'}'}\n<b>Bot:</b> {'{'}reply{'}'}\n\n"
app = pn.Column("## OrderBot",
pn.Row(msg := pn.widgets.TextInput(), pn.widgets.Button(name="Send", on_click=on_send)),
log := pn.pane.Markdown(""))
- Margherita — classic cheese and tomato
- Pepperoni — pepperoni and cheese
- Veggie Delight — peppers, onions, olives
- BBQ Chicken — BBQ sauce, chicken, onions
Would you like to order one of these?
Full Textbooks, Pre-Loaded and Ready to Go
Assign a notebook and learners are coding within minutes — no setup, no file distribution.
Have a Jupyter-based textbook of your own? Alps can onboard any Jupyter book as an interactive course. Get in touch.
Purpose-Built for Teaching
See how Alps Notebooks compare to traditional Jupyter infrastructure.
| Feature | Alps | Other Platforms |
|---|---|---|
| Zero setup — open browser and code | ||
| $0 per learner kernel | ||
| ~2 second kernel startup | ||
| Works on Chromebooks and tablets | ~ | |
| Notebooks inline with curriculum | ||
| One-click view of any learner's work | ||
| Progress analytics and attempt tracking | ||
| Built-in code diff against starter code | ||
| Secure browser sandbox — no OS access | ~ | |
| ipywidgets with real-time callbacks | ||
| IPython magics (%pip, %timeit, %who) | ||
| Local file upload + Google Drive access | ~ | |
| NumPy, Pandas, Matplotlib, Plotly |
Ready to Simplify Your Data Science Class?
Teach data science with Alps Notebooks, without the infrastructure headaches.