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.
Overview
Syllabus
Course 1: Health Data Science Foundation
- Offered by University of Illinois Urbana-Champaign. This course is intended for persons involved in machine learning who are interested in ... Enroll for free.
Course 2: Deep Learning Methods for Healthcare
- Offered by University of Illinois Urbana-Champaign. This course covers deep learning (DL) methods, healthcare data and applications using DL ... Enroll for free.
Course 3: Advanced Deep Learning Methods for Healthcare
- Offered by University of Illinois Urbana-Champaign. This course covers deep learning (DL) methods, healthcare data and applications using DL ... Enroll for free.
- Offered by University of Illinois Urbana-Champaign. This course is intended for persons involved in machine learning who are interested in ... Enroll for free.
Course 2: Deep Learning Methods for Healthcare
- Offered by University of Illinois Urbana-Champaign. This course covers deep learning (DL) methods, healthcare data and applications using DL ... Enroll for free.
Course 3: Advanced Deep Learning Methods for Healthcare
- Offered by University of Illinois Urbana-Champaign. This course covers deep learning (DL) methods, healthcare data and applications using DL ... Enroll for free.
Courses
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This course covers 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.
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This course covers 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.
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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.
Taught by
Jimeng Sun
