Intermediate · Short courseOnline · live classesOn campus
Computer Vision
Make machines see — image classification, object detection and segmentation with modern deep learning.
Enroll nowApproved & recognised by the University of Mysore
Level
Intermediate
Duration
10 weeks
Time commitment
7–9 hrs/week
Format
Live online or on campus
About this course
From reading pixels to production vision systems. You start with image fundamentals and classical techniques, move quickly into CNNs and modern architectures, and practise the three core tasks of applied vision: classification, detection and segmentation. Projects use real camera data — the messy kind — and the capstone deploys a working vision model behind a simple app.
Who it's for: Learners with Python and basic ML who want a specialisation employers can see working.
What you'll learn
Process and augment image data properly
Train CNN classifiers with transfer learning
Build object detection with YOLO-family models
Apply segmentation to real scenes
Deploy a vision model behind a live demo app
Syllabus
Image foundations
Weeks 1–2- Pixels, channels, filters
- OpenCV essentials
- Datasets and augmentation
Classification
Weeks 3–5- CNN architectures
- Transfer learning
- Reading confusion matrices
Detection & segmentation
Weeks 6–8- YOLO object detection
- Semantic segmentation
- Working with video
Capstone
Weeks 9–10- A deployed vision project
- Edge cases and failure analysis
- Demo day
Tools you'll use
PyTorchOpenCVYOLORoboflowGradio
Certificate
Finish the course and its capstone project to earn a FuturAIse Academy Certificate of Completion — verifiable online, with the projects to back it up.