This course is intended for persons involved in machine learning who are interested in medical applications, or vice versa, medical professionals who are interested in the methods modern computer science has to offer to their field. We will cover health data analysis, different types of neural networks, as well as training and application of neural networks applied on real-world medical scenarios.

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We cover deep learning (DL) methods, healthcare data and applications using DL methods. The courses include activities such as video lectures, self guided programming labs, homework assignments (both written and programming), and a large project.

The first phase of the course will include video lectures on different DL and health applications topics, self-guided labs and multiple homework assignments. In this phase, you will build up your knowledge and experience in developing practical deep learning models on healthcare data. The second phase of the course will be a large project that can lead to a technical report and functioning demo of the deep learning models for addressing some specific healthcare problems. We expect the best projects can potentially lead to scientific publications.

Course 1 of 3 in the Deep Learning for Healthcare Specialization.

Syllabus

WEEK 1

Introduction

In the introduction we will introduce the topic of the course and present the background information.

WEEK 2

Health Data

Health Data are generated in many different categories of medical services. We'll take a closer look at these, and what this means for Health Data standards.

WEEK 3

Machine Learning Basics

WEEK 4

Deep Neural Networks (DNN)

Deep Learning for Healthcare Specialization

Health Data

Machine Learning

Health Data Analytics

Deep Learning

Unsupervised Learning