This course is part of the Deep Learning for Healthcare Specialization

Jimeng Sun

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Associated with the Master of Computer Science degree
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Deep Learning for Healthcare SpecializationUniversity of Illinois at Urbana-Champaign

About this Course

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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.
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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 1 of 3 in the

Deep Learning for Healthcare Specialization

Advanced Level

We recommend a solid foundation in one of the fields adjacent to the topic of the course, such as Computer Science, Machine Learning, Medicine.

Approx. 24 hours to complete

English

What you will learn

Machine Learning, Health Data Processing

Skills you will gain

Graphs
Unsupervised Learning
Autoencoder
Deep Learning

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 1 of 3 in the

Deep Learning for Healthcare Specialization

Advanced Level

We recommend a solid foundation in one of the fields adjacent to the topic of the course, such as Computer Science, Machine Learning, Medicine.

Approx. 24 hours to complete

English

Instructor

Instructor rating

4.75/5 (5 Ratings)

Jimeng Sun

Professor

Computer Science Department

4,202 Learners

4 Courses

Offered by

University of Illinois at Urbana-Champaign

Start working towards your Master's degree

This course is related to the 100% online Master of Computer Science from University of Illinois at Urbana-Champaign. It will provide you with a preview of the topics, materials and instructors so you can decide if the full online degree program is right for you.

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Syllabus - What you will learn from this course

Week1

Week 1

6 hours to complete

Week 1 - Introduction

6 hours to complete

3 videos (Total 26 min), 3 readings, 2 quizzes

Week2

Week 2

6 hours to complete

Week 2 - Health Data

6 hours to complete

8 videos (Total 73 min), 3 readings, 2 quizzes

8 videos

Health Data - Introduction5mHealth Data: EHR, Notes12mHealth Data: Claims, Signals9mHealth Data: Images, Literature, Drugs11mHealth Data Standards: Intro & ICD11mHealth Data Standards: CPT, LOINC, NDC7mHealth Data Standards: SNOMED8mHealth Data Standards: UMLS6m

3 readings

Slides: Health Data30mSlides: Health Data Standards10mTextbook Chapter 2 (Health Data)1h

1 practice exercise

Health Data 30m

Week3

Week 3

6 hours to complete

Week 3 - Machine Learning Basics

6 hours to complete

9 videos (Total 89 min), 4 readings, 2 quizzes

9 videos

Prediction Target6mCohort Construction11mFeature Construction9mPredictive Model and Evaluation7mDimensionality Reduction10mClustering5mPerformance Metrics18mClassification Metrics6mRegression and Clustering Metrics13m

4 readings

Slides: Supervised Learning10mSlides: Unsupervised Learning10mSlides: Evaluation10mTextbook Chapter 3 (Machine Learning Basics)1h

1 practice exercise

Machine Learning Basics30m

Week4

Week 4

6 hours to complete

Week 4 - Deep Neural Networks (DNN)

6 hours to complete

4 videos (Total 37 min), 2 readings, 2 quizzes

About the Deep Learning for Healthcare Specialization

This specialization 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.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Health Data Science Foundation

About this Course

What you will learn

Skills you will gain