Due to the lapse in federal funding, this website will not be actively managed. More info. Neural Networks Online, Self-Paced Neural Networks Online, Self-Paced Course Description Due to recent advancements in processing, neural networks have become easier to train, which made them extremely popular. In this course, you will learn about neural networks and how to use them. Learning Objectives Introducing Neural Networks (NNs)start the coursedescribe neural networks and their capabilitiesdescribe how different neural networks are structureddescribe how cost functions are used to train neural networksdescribe activation functions and list different types of commonly used activation functionsdescribe feedforward neural networks and the intuition behind calculating gradients in neural networksdescribe how to use backpropagation for more efficient neural network trainingdescribe batch learning and why it makes neural network training easierTensorFlow (TF)describe TensorFlow and its high-level architectureset up TensorFlow for use on a CPUimport data into TensorFlow using built-in data sources and external data sourcesbuild and train a single-layer neural network in TensorFlowbuild and train a multilayer neural network in TensorFlowPractice: Neural Networksdescribe neural networks, network layers, cost functions, activation functions, and gradient descent Framework Connections The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework. Software Development Technology R&D Feedback If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.