An introduction to machine learning engineering, with a focus on neural networks. The entire process of developing a machine learning solution, from data collection to software development, as well as ethics in machine learning, will be discussed. Practical techniques in machine learning will be covered, including data augmentation and the use of pre-trained networks. Topics covered will include the fundamentals of neural networks, convolutional neural networks, recurrent neural networks, generative adversarial networks and transformer networks. Students will complete a major hands-on project in machine learning.