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This course is part of Deep Learning for Healthcare Specialization
Instructor: Jimeng Sun
4,541 already enrolled
Included with
Recommended experience
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.
Recommended experience
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.
Machine Learning, Health Data Processing
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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.
In the introduction we will introduce the topic of the course and present the background information.
3 videos3 readings1 assignment1 programming assignment1 discussion prompt
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.
8 videos3 readings1 assignment1 programming assignment
The topic of this week is Machine Learning. We'll look at
9 videos4 readings1 assignment1 programming assignment
4 videos2 readings1 assignment1 programming assignment1 plugin
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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Taking this course by University of Illinois Urbana-Champaign may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
Taking this course by University of Illinois Urbana-Champaign may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.
University of Illinois Urbana-Champaign
Degree · 1 – 3 years
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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.
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.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
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.