AI Labs & Robotics

Real problems.
Real products.

Two tracks — AI / ML engineering and Robotics & IoT. Real hardware, real datasets, real deployment environments. A community of serious builders who won't let you take shortcuts.

2
Lab tracks
12+
Active sprints
6
Ecosystems addressed
100%
Deployed — not simulated
Join the Labs View Curriculum
AI Lab

Not a classroom.
A proper workshop.

Everything you need to go from model idea to deployed product — in a community that will push you harder than you'd push yourself.

Weekly Model Sprints

Every week, the Labs run a focused experiment — a new model architecture, a new dataset, a real deployment challenge. You show up, you build, you share results. The pace is deliberate.

Shared GPU Compute

Serious model training requires serious hardware. Lab members get access to shared GPU resources so you can run the experiments that matter — without worrying about your cloud bill.

Global Dataset Library

A curated library of real-world datasets — agriculture, health, financial services, natural language. Real data from real contexts globally. Cleaned, documented, and ready for production-grade experiments.

Experiment Tracking

Shared MLflow and W&B workspaces so you can version runs, compare results, and build intelligently on each other's work. Science requires records.

Domain Expert Pairing

Every sprint pairs AI engineers with domain experts who understand the problem firsthand. Context — not just code — is the variable most AI projects get wrong.

Monthly Lab Showcases

Once a month, teams demo working software. Not slides, not decks — deployed products. The best work moves into the incubation pipeline. The rest teaches the whole community something real.

AI Lab — Recent sprints

What we've been building.
Week by week. No breaks.

Every sprint is a real problem, a real dataset, and a deployed result. Here's what the Lab shipped in the last cycle.

Sprint 01AgriAI

Build a RAG-powered assistant for agricultural extension workers using satellite and soil data

Sprint 02Fintech AI

Train a multilingual text classifier on real customer support tickets from a global fintech platform

Sprint 03AgriAI

Fine-tune a vision model to detect crop disease from smartphone photos in low-bandwidth environments

Sprint 04HealthAI

Deploy a speech-to-text API supporting low-resource languages with limited training data

Sprint 05PropTech

Build an LLM-powered property valuation engine from unstructured listing and transaction data

Sprint 06Fintech AI

Design a real-time fraud detection system for mobile money and digital wallet transactions at scale

Every sprint is open.
Every result is shared.

Lab members work in the open — failed experiments included. The fastest way to grow is to build alongside people who are doing the same hard thing.

Lab access is free.

Included with every AI School membership. Just show up and build.

Join the Labs
Robotics & IoT Track

Build systems that
touch the physical world.

Software alone cannot solve the challenges facing agriculture, healthcare, infrastructure, and conservation. This track teaches you to deploy intelligence into the real world — through hardware that senses, decides, and acts.

You will design sensor networks, write production firmware, build real-time data pipelines, and deploy systems that operate under genuine constraints — unreliable power, no connectivity, harsh environments, and communities that depend on uptime.

6
Ecosystems addressed
12+
Hardware platforms
48h
Sprint delivery window
100%
Deployed — not simulated
What you'll learn to build

Six capabilities.
One physical world.

The IoT track covers every layer of the stack — from firmware on the chip to dashboards in the operations centre.

Embedded Systems Programming

Write production firmware in MicroPython and C++ for Raspberry Pi, ESP32, and Arduino. Learn to think in microseconds, interrupts, and memory constraints — not abstractions.

Sensor Networks & Edge Computing

Design distributed sensor arrays that pre-process data at the edge. Understand power budgets, duty cycles, and why sending raw data to the cloud is always the wrong answer.

Real-Time Data Pipelines

Stream telemetry through MQTT brokers into time-series databases. Turn 10,000 sensor readings per minute into actionable operational intelligence.

Robotics Integration

Control servos, motors, and actuators with precision. Combine computer vision with ROS2 to build robots that perceive their environment and make real decisions.

Remote Monitoring Dashboards

Build operational dashboards in Grafana and Node-RED that field teams trust with their lives. Real-time alerting, anomaly detection, and multi-site visibility across unreliable networks.

Field Deployment Challenges

The lab simulates real-world constraints: intermittent connectivity, solar power budgets, dust, humidity, and hardware that fails at 3am. Build systems that work — not just in the lab.

Robotics & IoT — Active challenges

Critical problems.
Hardware that solves them.

Each challenge addresses a real failure point in a critical ecosystem. You are not building a demo. You are building the system that a community, hospital, or farm will depend on.

Challenge 01AgriTech

Deploy a 12-node soil NPK and moisture sensor array that autonomously triggers precision irrigation — cutting water use by 40%

Challenge 02HealthTech

Build a wearable vitals monitor (SpO2, ECG, temp) that streams patient data to a clinic dashboard over LoRa in zero-connectivity rural zones

Challenge 03Smart City

Architect a 10-node urban air quality mesh that detects PM2.5 spikes in real time and routes alerts to city health systems automatically

Challenge 04Industrial IoT

Attach vibration sensors to industrial motors and build an ML pipeline that predicts bearing failure 72 hours before it occurs

Challenge 05Conservation

Deploy solar-powered acoustic sensors in a protected wildlife reserve that detect and geolocate gunshots within 500m — in under 4 seconds

Challenge 06CleanTech

Install CT clamps on household mains feeds and build a disaggregation model that identifies every appliance and calculates its real-time carbon cost

Hardware kits available
for Lab members.

Don't have hardware? The Lab maintains a shared kit program. Sensors, microcontrollers, and prototyping components shipped to active members for the duration of each challenge.

Both tracks. One membership.

AI Lab and the Robotics & IoT track are included with every AI School membership. No extra cost.

Join the IoT Track

The Robotics & IoT stack you'll master

Raspberry Pi
Edge compute node
ESP32
WiFi / BLE MCU
Arduino
Prototyping hardware
MicroPython
Firmware scripting
MQTT
Device messaging
Node-RED
Flow-based IoT logic
InfluxDB
Time-series store
Grafana
Ops dashboards
AWS IoT Core
Device management
ROS 2
Robotics framework
LoRaWAN
Long-range mesh
OpenCV
Robot vision

The AI production stack you'll master

Python
The language of AI
HuggingFace
Models & datasets
LangChain
LLM orchestration
FastAPI
Model serving
Docker
Containerisation
AWS / GCP
Cloud deployment
MLflow
Experiment tracking
PostgreSQL
Vector + relational DB
Who can join

Lab access is for
serious builders.

You don't need to be an expert. You need to be willing to show up, run experiments, and learn in public — even when your model doesn't converge or your sensor gives the wrong reading at 3am.

Active TechOps Hub membership ($15 / $29 one-time)
Enrolled in the AI Product School or Technical Writing
A working laptop and reliable internet connection
The willingness to fail, share, and iterate in public

Lab access is free.

Both tracks — AI Lab and Robotics & IoT — are included with every AI School membership. No extra cost. Just show up.

Join the Labs

The next sprint starts
when you show up.

AI, Robotics, IoT — the problems are real. The hardware is real. The community will not let you take shortcuts. Show up and build something that matters.

Get Lab Access