I plan to first start with the idea of CNNs and why they should be used when we already have common or dense NNs. I would then move on to show the clear win which CNN creates for image classification as it is all about picking out features. I then plan to show attendees how an image journeys through convolutional layers and how it extracts features, I would also show them a visualization of the same. Having done this I plan to show the attendees how TensorFlow makes it easy to load and label images in the runtime, I would also show them the use of image augmentation with TF and how it works in TF to save resources in the disk space and also dropouts to reduce potential overfitting. Then, I plan to show them how to use the indispensable Transfer Learning so we can efficiently utilize the work done by other people. At the last I also plan to show the different output layers one should use for binary classification and categorical.