AI on the Edge shows you how artificial intelligence works outside the cloud — on a small computer with a camera, making decisions in real time. You train and run computer-vision models on a Raspberry Pi and connect them to real outputs such as alarms, displays and motors.
The course balances understanding with building. You learn how image models work, then put them to work in practical projects like a face-recognition attendance system and an object-counting camera.
Who this course is for
- Engineering, B.Sc and BCA/MCA students with basic programming knowledge
- Robotics and IoT learners who want to add intelligence to their projects
- Professionals exploring practical computer vision and edge AI
What you will learn
- Python for AI: NumPy, Pandas and Matplotlib
- Machine-learning basics: datasets, training, testing and accuracy
- Image processing with OpenCV: filters, contours and colour tracking
- Neural networks and transfer learning with TensorFlow / Keras
- Converting models to TensorFlow Lite and running them on Raspberry Pi
- Using GPIO to connect AI decisions to LEDs, buzzers and motors
Course plan
Week 1: Python and data
Python refresher, working with data in NumPy and Pandas, and plotting results.
Week 2: Machine learning fundamentals
Train simple classifiers, understand overfitting and measure accuracy properly.
Week 3: Computer vision with OpenCV
Capture camera frames, detect faces, track colours and count objects.
Week 4: Deep learning on the edge
Train an image classifier with transfer learning and deploy it with TensorFlow Lite on the Raspberry Pi.
Week 5: Capstone project
Build and present a complete edge-AI system that reacts to what the camera sees.
Projects you will build
- Face-detection and recognition attendance system
- Object detection and counting camera
- Gesture- or colour-controlled device using GPIO
Tools and hardware
Raspberry Pi 4, Pi Camera or USB webcam, microSD card, LEDs, buzzer, servo motor and breadboard, plus Python, OpenCV, TensorFlow / Keras and TensorFlow Lite. Hardware is provided for lab sessions.
Prerequisites
Basic programming in any language (Python preferred) and school-level maths. If you are new to Python, we share a short preparation module before the batch starts.
After the course
Continue with the AI & ML Internship to work on a larger computer-vision or data project, or combine AI with our Robotics and IoT programs.
Frequently asked questions
Do I need a powerful laptop?
No. Heavy training runs on free cloud notebooks, and models run on the Raspberry Pi provided in the lab.
Is advanced maths required?
No. We explain the intuition behind the models; school-level maths is enough to follow along.
Will I understand AI or just copy code?
You will understand it. Every project starts with why a technique works before you implement and test it yourself.
Fees, batch timings and seat availability are shared on enquiry. Message us on WhatsApp or use the enquiry form, and our team will help you choose the right batch.
