• Online, Instructor-Led
  • Online, Self-Paced

This module provides lectures and labs on deep learning and machine learning using combination of tools such as cognitive services APIs, Deep Learning frameworks and libraries. Two major breakthroughs for cognitive computing in healthcare are: 1) consumer/user engagement (e.g. example IBM Watson social network Welltok) and 2) discovery applications, such as drug discovery and analysis of human health. Internet of Medical Things integrates sensors and AI algorithms, which are vulnerable to cyber-attacks. Examples of attacks are: 1) access by malicious actors; 2) loss or corruption of enterprise information and patent data. Topics include: Neural Networks, Convolutional Neural Network (CNN), Long – Short Term

Learning Objectives

Understanding how different Deep Learning models work and the difference between Cognitive Computing, Machine Learning and Artificial Intelligence. Analyze multiple data types such as images and text. Perform anomaly detection using Autoencoder, Understanding Text Analysis, Perform analysis of case studies related to cybersecurity and healthcare.

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Work Roles