EducationRaspberry PiCurriculum

Classroom Projects: Teach Programming with Raspberry Pi, Micro Apps, and Mapping APIs

UUnknown

2026-02-17

10 min read

A semester curriculum that combines Raspberry Pi, micro apps, and mapping APIs so students build deployable projects and product thinking.

Hook: Turn scattered theory into portfolio-ready projects this semester

Teachers: tired of fragmented, outdated web dev units that never produce real portfolio pieces? Students: frustrated that courses teach syntax but not product thinking or deployment? This semester-long curriculum marries hands-on hardware (Raspberry Pi), fast, focused micro apps, and modern mapping APIs so each learner graduates with deployable projects, demo-ready code, and a simple product mindset.

The 2026 context — why this mix matters now

Late 2025 and early 2026 brought three shifts that make this curriculum timely and practical:

Raspberry Pi 5's ecosystem matured and an AI HAT+ for on-device generative AI arrived, enabling lightweight local inference for classroom demos (ZDNET, 2025).
Micro apps became mainstream: quick, single-purpose web apps built by non-experts using AI-assisted workflows are now common (TechCrunch, 2024–2025) — ideal for semester projects.
Mapping APIs evolved: improved vector-tile performance, more affordable tiers, and robust open-source alternatives (MapLibre, OpenStreetMap tooling) let students build interactive maps without enterprise budgets.

Put together, these trends let you teach full-stack thinking — from sensors to UI to deployed micro app — in a way that produces tangible outcomes within a typical academic term.

Curriculum overview — semester roadmap (14 weeks + capstone)

This outline is designed for a 14-week semester with a final 1–2 week capstone. Each week includes objectives, activities, deliverables, and a short teacher note. Mix Python and Node.js tracks depending on your classroom background; both tracks are parallel and interoperable.

Learning outcomes

Students will build 2–3 deployable micro apps that incorporate mapping features (geocoding, markers, heatmaps, routing).
Students will connect Raspberry Pi sensors and/or cameras to a backend and visualize live data on maps.
Students will practice product thinking: user stories, MVP scope, iterative testing, and deployment.
Students will learn basics of Python and/or Node.js server development, REST/WebSocket APIs, HTML/CSS/JS, and hosting strategies.

Weekly breakdown (detailed)

Week 1 — Kickoff & product thinking

Objectives: introduce micro apps, mapping use-cases, and Raspberry Pi capabilities. Start small: a one-week micro app mindset.

Activity: rapid idea storm — generate 20 micro app ideas (e.g., "Where to study on campus", "Bike rack availability map").
Deliverable: select a project idea and write a one-paragraph user story and three acceptance criteria.

Week 2 — Tools & templates setup

Objectives: install tools, create starter repos, and walk through the basic Pi setup.

Teacher note: provide two starter branches — Python (Flask/FastAPI) and Node.js (Express). Include a basic HTML/CSS/JS scaffold with a Leaflet or MapLibre map placeholder.
Activity: Raspberry Pi image flash, SSH setup, and (optional) AI HAT+ demo. Show how a Pi can host local services and collect sensor data.
Deliverable: working repo fork and Pi network connectivity check.

Week 3 — HTML, CSS, and interactive mapping basics

Objectives: teach DOM basics, responsive layout, and integrate a mapping library (Leaflet or MapLibre GL JS).

Activity: build a map that shows static markers using GeoJSON. Introduce vector vs raster tiles and API key management.
Deliverable: publish static map page to GitHub Pages or a preview URL. Consider lightweight storage tiers or cloud NAS for media assets during demos.

Week 4 — JavaScript fundamentals & client-side APIs

Objectives: ES6 modules, fetch(), Promises, and simple UI state.

Activity: fetch a JSON dataset (campus buildings) and render markers with popups. Add a search filter.
Deliverable: searchable interactive map micro app.

Week 5 — Backend basics: Python vs Node.js

Objectives: introduce routes, JSON endpoints, and a simple REST API.

Activity (Python): build a Flask/FastAPI endpoint that returns sample sensor data. (Node.js): build Express route that serves dataset.
Deliverable: client map fetches live data from the local backend.

Week 6 — Raspberry Pi sensors & telemetry

Objectives: connect a temperature sensor, light sensor, or simple PIR motion sensor to Raspberry Pi GPIO; send data to backend.

Activity: write a Python script (or Node.js script) that reads sensor values and POSTs to backend every N seconds. Demo: camera snapshot upload for a photo map (see local dev camera reviews for affordable hardware options).
Deliverable: map displays latest sensor values or snapshots at marker locations.

Week 7 — Real-time updates & WebSockets

Objectives: show WebSocket basics or Server-Sent Events to push sensor updates to clients.

Activity: convert the previous app to show live telemetry on the map using socket messages. Implement throttling and simple auth token for safety. See edge orchestration patterns for real-time routing and security.
Deliverable: live-updating heatmap or realtime marker updates.

Week 8 — Micro apps ergonomics & UX

Objectives: teach minimal UX patterns tailored to micro apps: clear primary action, quick onboarding, Progressive Web App (PWA) basics.

Activity: wireframe a micro app flow, implement a minimal onboarding modal, add installable PWA manifest.
Deliverable: micro app passes a simple UX checklist and PWA install test.

Week 9 — Mapping APIs advanced: routing, geocoding, and tiling

Objectives: introduce geocoding services, routing APIs, and vector tile customization. Discuss privacy, API key quotas, and open-source alternatives (MapLibre + OSM).

Activity: add a route-drawing feature that queries a routing API (OSRM / GraphHopper / commercial provider). Add address search via Nominatim or a paid geocoding provider.
Deliverable: map can compute and display a route between two user-input addresses.

Week 10 — Data processing & spatial analysis (Turf.js)

Objectives: teach basic geospatial analysis — buffers, clustering, heatmaps, nearest neighbor.

Activity: use Turf.js (client-side) to compute areas of influence, or perform server-side geometry ops with Shapely (Python) or turf/geojson-utils (Node.js).
Deliverable: map visualization includes a heatmap and a "near me" feature.

Week 11 — Authentication, data privacy, and API costs

Objectives: teach safe handling of API keys, student data privacy, and cost-awareness for mapping services.

Activity: move API keys off client into a small server-side proxy. Run a cost simulation comparing commercial vs open-source mapping options.
Deliverable: secure key handling and a short cost report for the chosen APIs. Consider object storage for tiles and media when budgeting (object storage guide).

Week 12 — Deployment options & CI basics

Objectives: expose students to modern deployment choices: static hosting (GitHub Pages, Netlify), server hosting (Render, Railway, Fly.io), and edge devices (Raspberry Pi local server).

Activity: pick one target (student choice) and deploy a micro app with automated deploys via GitHub Actions; optionally set up a Pi as a local staging server. Use cloud pipelines and local testing patterns to keep releases safe and repeatable.
Deliverable: live URL and CI workflow file in repo. See cloud pipeline case studies for CI ideas.

Week 13 — Monetization & sustainment (mini-business thinking)

Objectives: introduce simple monetization models for micro apps and maintenance plans for small clients (student clubs, local shops).

Activity: student teams pitch a monetization plan or a community deployment strategy (ads, subscriptions, sponsored features, volunteer-hosted Pi nodes).
Deliverable: 5-minute pitch video and one-page plan.

Week 14 — QA, polish, and demo preparation

Objectives: final polish, accessibility checks, mobile testing, and prep for demo day.

Activity: run Lighthouse audits, test on mobile, fix core UX bugs, rehearse demos. Use hosted tunnels and local testing patterns to demo devices in class reliably.
Deliverable: final demo-ready micro app and repository with README and deployment link.

Capstone (Week 15–16) — Showcase & reflection

Capstone deliverables combine hardware, micro app, and mapping API: examples include a "Campus Air Quality Map" using Pi sensors, a "Bike Availability Micro App" with routing suggestions, or a community "Event Map" with real-time check-ins.

Deliverables: working app, deploy URL, 3-minute demo, and a retrospective documenting choices, trade-offs, and next steps.

Sample project: Live Heatmap from Raspberry Pi sensors (teacher-tested)

This is a compact, high-impact class project tested in two fall terms. It demonstrates hardware integration, backend APIs, WebSockets, and mapping visualizations.

Hardware: a Pi 5 (or Pi 4) with a DHT22 temperature sensor or DS18B20. Optionally use multiple Pis for different campus locations. For camera options, check affordable local-dev camera reviews like the PocketCam Pro review.
Data flow: sensor → local Python script → POST to backend → backend forwards via WebSocket → client map updates heatmap layer.
Deployment: backend on Render or Fly.io, static frontend on GitHub Pages or Vercel, Pis configured with a secure token to authenticate POST requests. Use hosted tunnels and local testing to simplify classroom networking (dev ops patterns).

Quick starter pseudo-code (Python sensor loop):

# sensor_loop.py (concept)
import requests
import time

API_URL = 'https://your-backend.example.com/telemetry'
TOKEN = 'SENSOR_TOKEN'

while True:
    temp = read_temp_sensor()
    payload = { 'device_id': 'pi-01', 'temp': temp, 'lat': 40.0, 'lng': -74.0 }
    headers = { 'Authorization': f'Bearer {TOKEN}' }
    requests.post(API_URL, json=payload, headers=headers)
    time.sleep(30)

On the frontend use a heatmap plugin and WebSocket messages to update a GeoJSON layer in real-time.

Assessment and grading rubrics

Keep assessment simple and focused on outcomes. Suggested weights:

Project deliverables & demo (50%) — functionality, UI, and deployment
Product thinking pack (20%) — user story, wireframe, MVP scope
Code quality & documentation (15%) — README, comments, test cases
Reflection and team contribution (15%) — retrospective and peer review

Starter templates & resources (teacher toolkit)

Provide students with small, commented starter repos and one-page cheat sheets. Include:

HTML/CSS/JS map scaffold (Leaflet + MapLibre fallback)
Flask and Express starter repos with JWT auth and WebSocket examples
Raspberry Pi sensor examples (Python) and Pi image checklist
CI template for GitHub Actions to deploy frontend and backend — see cloud pipeline case studies for automated deploy patterns.
Short videos on API key safety and cost estimation

Teaching tips and common pitfalls

Start small: require an MVP first, then add mapping or Pi features as stretch goals.
API costs: reserve a paid map API key for the class, set usage alerts, and teach students how to switch to MapLibre/OpenStreetMap during demos.
Hardware reliability: have spare Pis and pre-flashed SD cards to avoid wasted class time.
Safety & privacy: never publish student locations without explicit consent. Use synthetic or anonymized data for public demos. Campus deployments should follow campus health and privacy playbooks.
Balance languages: let students choose Python or Node.js but have interoperable endpoints so team members can mix stacks.

Extensions & future-proofing (2026+)

Push advanced students toward these 2026-forward topics:

On-device AI inference on Raspberry Pi 5 with AI HAT+ for features like smart labels or summarization at the edge.
Offline maps and progressive sync for fieldwork apps using vector tile caches.
Edge functions and serverless routing to lower latency for real-time sensor feeds (Fly.io, Cloudflare Workers).
Integrating LLM-assisted code helpers to turn user stories into scaffolded code — teach prompt validation and debugging instead of blind reliance.

Case study: Campus Garden Heatmap (real-world example)

In a pilot taught in Fall 2025, 28 students built a "Campus Garden Heatmap":

Hardware: three Pis with soil moisture sensors across garden plots.
Software: Node.js backend, WebSocket stream, frontend using MapLibre and Turf.js.
Outcome: a functioning micro app, deployed on Fly.io, used by the campus horticulture club to optimize watering schedules. Students added a small donation button to fund Pi maintenance.

This project demonstrates experience-driven learning: the team learned API budgeting, device maintenance, and user interviews while producing something the community used.

"Teaching programming works best when students build things people care about. A Pi, a tiny web app, and a map create that loop." — Curriculum lead, pilot cohort, 2025

Actionable checklist to start this semester

Acquire hardware: 1 Pi per 2 students, sensors (DHT22, DS18B20), optional AI HAT+ for advanced groups.
Fork starter repos and prepare one demo that works end-to-end (Pi → backend → map). Use cloud NAS or object storage for large media when necessary (cloud NAS guide, object storage options).
Reserve a small budget for mapping API credits or plan for MapLibre + OSM.
Create a simple grading rubric and publish it in week 1.
Schedule a demo day and invite community stakeholders (student clubs, local businesses).

Final takeaways (what students leave with)

Practical skills: HTML/CSS/JS, Python or Node.js backends, WebSockets, and basic geospatial analysis.
Deployment experience: CI-driven deployment and simple hosting choices for micro apps. See cloud pipeline case studies for CI patterns.
Product instincts: MVP scoping, rapid prototyping, and iteration through user feedback.
Portfolio-ready outputs: two deployable micro apps with mapping features and a capstone integrating hardware.

References & further reading

ZDNET coverage of Raspberry Pi 5 hardware updates and AI HAT+ (late 2025)
TechCrunch reporting on the rise of micro apps and rapid personal app building (2024–2025)
MapLibre, OpenStreetMap, Turf.js, OSRM, GraphHopper documentation for mapping tools

Call to action

Ready to run this in your classroom? Download the free semester syllabus, starter repos, grading rubrics, and a teacher checklist at webbclass.com/curriculum. Sign up for a live walkthrough where we’ll deploy the sample heatmap together and answer your setup questions. For practical device recommendations and tests, check local dev camera reviews and cloud NAS options to avoid surprise storage or bandwidth costs.

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