How does a machine actually learn? Stepping away from abstract mathematical equations, this interactive lab offers a fully visual, zero-code experience of training an artificial intelligence. You will gather real data, watch a model train in real time, and intuitively grasp where algorithmic biases, accuracy, and limitations truly come from.
What you will gain
- Visual training with zero code
- Intuitive grasp of algorithmic bias
- Working model built by each participant
Target outcomes
- Train an operational visual model with zero code
- Understand machine learning lifecycle from data to inference
- Recognize dataset biases and data quality importance
Prerequisites
- No technical prerequisites.
Detailed Curriculum
Based on Course 5 (AI Experience):
- Module 1 — Lab 1: teaching a machine to recognize physical gestures and images; training data mechanics.
- Module 2 — Lab 2: number and image recognition, model inference, and boundaries; data bias & ethics module.
Educational & Business Use Cases
Interactive applications:
- Demystifying AI for non-technical teams and leadership
- Prototyping an intuitive visual AI concept for executive buy-in
- Introducing students and professionals to machine learning mechanics
Deliverables & Transversal Modules
Deliverable: A functional, trained machine learning model built by the participant.
Transversal modules: Psychology of Change · Ethics & EU AI Act.
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Instructor
Boutaina Aribia
Lead AI Trainer & Consultant
This training is designed to quickly turn understanding into execution capacity, with a clear, concrete and directly applicable format.
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Support Instructor
Noureddine Mohtram
Senior Cloud & AI Architect
This instructor participates in delivery and support to ensure personalized guidance for each student.
