Computer Vision Applications

Entry requirements

M01; Python arrays and image basics

What 36 hours means

Lessons

24 h

Capstone

8 h

Assessment

2 h

Remediation

2 h

Syllabus

Four modules, twelve lessons. Every lesson states what it covers and the evidence you produce for it.

• Module

  01

  3 lessons · 6 h

  

  Module 1

  Image foundations

  Images as arrays · Image preprocessing · Dataset annotation

  M02Show lessonsHide lessons▾

  1. M02.01 · 120 min

     Images as arrays

     Inspect resolution, colour channels and coordinate conventions.

     Evidence: Image transforms preserve expected shapes and channel order.

  2. M02.02 · 120 min

     Image preprocessing

     Apply resize, normalisation and contrast adjustments.

     Evidence: A comparison documents which transforms preserve task information.

  3. M02.03 · 120 min

     Dataset annotation

• Module

  02

  3 lessons · 6 h

  

  Module 2

  Learning models

  Data augmentation · Convolutional networks · Transfer learning

  M02Show lessonsHide lessons▾

  1. M02.04 · 120 min

     Data augmentation

     Apply training-only transformations suitable for the task.

     Evidence:

• Module

  03

  3 lessons · 6 h

  

  Module 3

  Detection

  Object detection · Segmentation concepts · Vision evaluation

  M02Show lessonsHide lessons▾

  1. M02.07 · 120 min

     Object detection

     Interpret boxes, confidence and overlapping detections.

     Evidence:

• Module

  04

  3 lessons · 6 h

  

  Module 4

  Deployment

  Latency optimisation · Privacy and robustness · Inference service

  M02Show lessonsHide lessons▾

  1. M02.10 · 120 min

     Latency optimisation

     Compare batch size and image resolution on inference time.

     Evidence:

Capstone

Develop a visual inspection prototype using approved images, including a held-out evaluation, failure analysis and an inference demonstration.

Lab environment

GPU notebook with CPU fallback

Lab infrastructure is not yet provisioned, so this describes the environment the course is designed for rather than one you can launch today.

Part of a pathway

• Intelligent Robotics Professional — as a prerequisite