Computer Vision

About this course

Develop a practical computer vision workflow for classification, object detection and segmentation, with attention to data quality and deployment.

This advanced course is part of the AI & Generative AI school. Work through the curriculum below in a instructor-led / cohort format, with an estimated study time of 28 h.

Course curriculum

• Module 1 — Images as Data and Classical Vision
• Module 2 — CNN Classifiers for Inspection
• Module 3 — Robustness and Distribution Shift
• Module 4 — Explainability and Shortcut Learning
• Module 5 — Object Detection
• Module 6 — Semantic Segmentation
• Module 7 — Labels, Data Quality and Active Learning
• Module 8 — Deploying Vision Models at the Edge

Applied learning

• Case study — Ferrox Precision: from pilot to production inspection
• Lab 1 — Camera changeover
• Lab 2 — Improving the detector
• Lab 3 — Stain grading, from mask to deployed decision
• Capstone — An Inspection Vision System

Who this course is for

Technology Professional; Data Professional; Engineer / Architect

Prerequisites

NE-AI-201

Course details

• Course code: NE-AI-303
• Level: Advanced
• Estimated duration: 28 h
• Delivery: Instructor-Led / Cohort