We may earn an affiliate commission when you visit our partners.
Colin Matthews
Deep learning is a powerful machine learning technique that has led to incredible innovations in artificial intelligence. This course will teach you the fundamentals of deep learning in healthcare through theory and applied case studies.
Read more
Deep learning is a powerful machine learning technique that has led to incredible innovations in artificial intelligence. This course will teach you the fundamentals of deep learning in healthcare through theory and applied case studies.
Read more
Deep learning is a powerful machine learning technique that has led to incredible innovations in artificial intelligence. This course will teach you the fundamentals of deep learning in healthcare through theory and applied case studies.
Deep learning is used daily to select the advertisements you see, drive product recommendations, and help you become more productive. In this course, Deep Learning Applications for Healthcare, you’ll understand how deep learning is changing healthcare through theory and applied case studies. First, you’ll explore the fundamentals of deep learning in healthcare. Next, you’ll discover how healthcare data is collected and structured. Finally, you’ll learn about common pitfalls when implementing machine learning in healthcare. When you’re finished with this course, you’ll have the skills and knowledge of Deep Learning Application for Healthcare needed to understand current and future applications of deep learning in this context.
Register for this course and see more details by visiting:
OpenCourser.com/course/yy9w6z/deep
Here's a deal for you
We found an offer that may be relevant to this course.
Save money when you learn.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
What's inside
Syllabus
Course Overview
Fundamentals of Deep Learning
Healthcare Data
Ethics in Healthcare AI
Read more
Syllabus
Course Overview
Fundamentals of Deep Learning
Healthcare Data
Ethics in Healthcare AI
Read more
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches the fundamentals of deep learning and its applications in healthcare
Utilizes applied case studies to demonstrate real-world implementations of deep learning in healthcare
Covers the process of collecting and structuring healthcare data, essential for deep learning models
Provides insights into the ethical considerations of using AI in healthcare
Developed by industry experts, Colin Matthews, ensuring the course content is up-to-date and relevant
May require prior knowledge in deep learning or healthcare data analysis
Save this course
Save Deep Learning Application for Healthcare to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Deep Learning Application for Healthcare with these
activities:
Organize Course Materials
Show steps
Well-organized materials will enhance your ability to locate and review important concepts throughout the course.
Show steps
-
Create a dedicated folder or notebook for course materials
-
Organize notes, assignments, quizzes, and exams into clear sections
-
Review and highlight key concepts from the course syllabus
Read Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Show steps
This book provides a comprehensive overview of machine learning techniques, including deep learning, with practical examples in healthcare.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
-
Read the chapters covering deep learning algorithms and their applications
-
Work through the code examples and exercises provided in the book
Practice Deep Learning Coding Exercises
Show steps
Regular practice with coding exercises will strengthen your comprehension of deep learning algorithms and enhance your programming skills.
Show steps
-
Solve coding challenges related to deep learning tasks such as image classification or natural language processing
-
Experiment with different deep learning libraries like TensorFlow or PyTorch
-
Debug and optimize your deep learning code
Two other activities
Expand to see all activities and additional details
Show all five activities
Join a Deep Learning Study Group
Show steps
Engaging with peers through study groups can foster collaboration, deepen your understanding, and expand your perspectives on deep learning in healthcare.
Show steps
-
Find or create a study group with fellow learners interested in deep learning
-
Establish regular meetings to discuss course concepts, share knowledge, and work on projects together
-
Engage in peer-to-peer teaching and learning
Explore Deep Learning Case Studies
Show steps
Case studies provide real-world examples of how deep learning is applied in healthcare, enhancing your understanding of its practical implications.
Browse courses on
Deep Learning Applications
Show steps
-
Review case studies that showcase the use of deep learning in healthcare settings
-
Analyze the challenges and benefits associated with these applications
-
Identify potential areas where deep learning can further contribute to the healthcare industry
Organize Course Materials
Show steps
Well-organized materials will enhance your ability to locate and review important concepts throughout the course.
Show steps
Show steps
Show steps
- Create a dedicated folder or notebook for course materials
- Organize notes, assignments, quizzes, and exams into clear sections
- Review and highlight key concepts from the course syllabus
Read Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Show steps
This book provides a comprehensive overview of machine learning techniques, including deep learning, with practical examples in healthcare.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
Show steps
Show steps
- Read the chapters covering deep learning algorithms and their applications
- Work through the code examples and exercises provided in the book
Practice Deep Learning Coding Exercises
Show steps
Regular practice with coding exercises will strengthen your comprehension of deep learning algorithms and enhance your programming skills.
Show steps
Show steps
Show steps
- Solve coding challenges related to deep learning tasks such as image classification or natural language processing
- Experiment with different deep learning libraries like TensorFlow or PyTorch
- Debug and optimize your deep learning code
Two other activities
Expand to see all activities and additional details
Show all five activities
Join a Deep Learning Study Group
Show steps
Engaging with peers through study groups can foster collaboration, deepen your understanding, and expand your perspectives on deep learning in healthcare.
Show steps
Show steps
Show steps
- Find or create a study group with fellow learners interested in deep learning
- Establish regular meetings to discuss course concepts, share knowledge, and work on projects together
- Engage in peer-to-peer teaching and learning
Explore Deep Learning Case Studies
Show steps
Case studies provide real-world examples of how deep learning is applied in healthcare, enhancing your understanding of its practical implications.
Browse courses on
Deep Learning Applications
Show steps
Show steps
Show steps
- Review case studies that showcase the use of deep learning in healthcare settings
- Analyze the challenges and benefits associated with these applications
- Identify potential areas where deep learning can further contribute to the healthcare industry
Career center
Learners who complete Deep Learning Application for Healthcare will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use deep learning to examine large datasets, using AI to uncover patterns and solve complex problems. This course will help you further hone your skills as a Data Scientist by providing you with the fundamentals of deep learning in healthcare. Additionally, you’ll further develop your knowledge of how healthcare data is collected and structured.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. They use deep learning to build AI systems that can learn from data and make predictions. This course will enhance your skills as a Machine Learning Engineer by providing you with the fundamentals of deep learning in healthcare. You'll learn how to collect and structure healthcare data, which will make you even more valuable to potential employers in this field.
Healthcare Data Analyst
Healthcare Data Analyst
Healthcare Data Analysts collect, analyze, and interpret data to improve the quality and efficiency of healthcare. They use deep learning to identify patterns and trends in healthcare data, which can help them make more informed decisions about patient care. This course will help you develop the skills you need to be a successful Healthcare Data Analyst. You'll learn how to collect and structure healthcare data, and you'll gain a foundation in deep learning.
Healthcare Consultant
Healthcare Consultant
Healthcare Consultants provide advice to healthcare organizations on how to improve their operations. They use deep learning to identify inefficiencies and develop solutions to improve patient care. This course will give you the skills you need to be a successful Healthcare Consultant. You'll learn how to collect and structure healthcare data, and you'll gain a foundation in deep learning.
Artificial Intelligence Architect
Artificial Intelligence Architect
Artificial Intelligence Architects design and develop AI systems that are used in a variety of applications, including healthcare. They use deep learning to develop AI systems that can learn from data and make predictions. This course will help you develop the skills you need to be a successful Artificial Intelligence Architect. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Healthcare Software Engineer
Healthcare Software Engineer
Healthcare Software Engineers design, develop, and maintain software for the healthcare industry. They use deep learning to develop software that can help improve the quality and efficiency of healthcare. This course will help you develop the skills you need to be a successful Healthcare Software Engineer. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Health Informatics Specialist
Health Informatics Specialist
Health Informatics Specialists use data and technology to improve the quality and efficiency of healthcare. They use deep learning to develop predictive models and decision-support tools that can help healthcare providers make better decisions about patient care. This course will help you develop the skills you need to be a successful Health Informatics Specialist. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Clinical Research Associate
Clinical Research Associate
Clinical Research Associates conduct clinical trials for new drugs and medical devices. They use deep learning to develop predictive models that can help identify patients who are at risk of developing certain diseases. This course will help you develop the skills you need to be a successful Clinical Research Associate. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Biomedical Engineer
Biomedical Engineer
Biomedical Engineers design and develop medical devices and systems. They use deep learning to develop AI systems that can be used to diagnose and treat diseases. This course will help you develop the skills you need to be a successful Biomedical Engineer. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Data Architect
Data Architect
Data Architects design and manage data systems. They use deep learning to develop data-driven applications that can help businesses make better decisions. This course will help you develop the skills you need to be a successful Data Architect. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make better decisions. They use deep learning to develop predictive models and decision-support tools that can help businesses identify new opportunities and avoid risks. This course will help you develop the skills you need to be a successful Data Analyst. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Software Architect
Software Architect
Software Architects design and develop software systems. They use deep learning to develop software that can learn from data and make predictions. This course will help you develop the skills you need to be a successful Software Architect. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Healthcare Administrator
Healthcare Administrator
Healthcare Administrators oversee the day-to-day operations of healthcare organizations. They use deep learning to develop data-driven solutions that can help improve the quality and efficiency of healthcare. This course will help you develop the skills you need to be a successful Healthcare Administrator. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Medical Physicist
Medical Physicist
Medical Physicists use their knowledge of physics to develop and use medical devices and systems. They use deep learning to develop AI systems that can be used to diagnose and treat diseases. This course will help you develop the skills you need to be a successful Medical Physicist. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
Biostatistician
Biostatistician
Biostatisticians use statistics to design and analyze clinical trials. They use deep learning to develop predictive models that can help identify patients who are at risk of developing certain diseases. This course will help you develop the skills you need to be a successful Biostatistician. You'll learn the fundamentals of deep learning, and you'll gain experience in applying deep learning to healthcare data.
For more career information including salaries, visit:
OpenCourser.com/course/yy9w6z/deep
Reading list
We've selected five books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Deep Learning Application for Healthcare.
Serves as a comprehensive textbook on machine learning fundamentals. Provides a solid theoretical foundation for understanding deep learning.
Provides an overview of machine learning methods and applications in healthcare, with a focus on challenges and opportunities.
Provides a hands-on introduction to machine learning using popular Python libraries. Serves as a good foundation for understanding the technical aspects of deep learning in healthcare.
Save
Provides a broad overview of deep learning methods and applications. Serves as a good reference for understanding the fundamentals of deep learning.
Provides a comprehensive overview of deep learning in healthcare, with a focus on cutting-edge research and applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/yy9w6z/deep
Share
Similar courses
Here are nine courses similar to
Deep Learning Application for Healthcare.
Machine Learning for Healthcare
OpenCourser.com/course/2sbyo2/machine
Machine Learning for Healthcare
Most relevant
Health Data Science Foundation
OpenCourser.com/course/4634gi/health
Health Data Science Foundation
Transfer Learning for Food Classification
OpenCourser.com/course/46xldi/transfer
Transfer Learning for Food Classification
Developing Clinical Empathy: Making a Difference in Patient Care
OpenCourser.com/course/7rnvp9/developing
Developing Clinical Empathy: Making a Difference in...
XR in Healthcare Education and Clinical Practice
OpenCourser.com/course/o9zaz3/xr
XR in Healthcare Education and Clinical Practice
Creative Problem Solving: Design Thinking in Health and Social Care
OpenCourser.com/course/t1chjx/creative
Creative Problem Solving: Design Thinking in Health and...
Process Mining in Healthcare
OpenCourser.com/course/7w8czg/process
Process Mining in Healthcare
AI-Powered Chest Disease Detection and Classification
OpenCourser.com/course/0kzoyp/ai
AI-Powered Chest Disease Detection and Classification
Healthcare Delivery Providers
OpenCourser.com/course/3mrxa3/healthcare
Healthcare Delivery Providers
Time
63 hours
Level
Introductory
Via
Pluralsight
Instructor
Colin Matthews
Language
English
Good to know
Teaches the fundamentals of deep learning and its applications in healthcare
Utilizes applied case studies to demonstrate real-world implementations of deep learning in healthcare
Covers the process of collecting and structuring healthcare data, essential for deep learning models
Provides insights into the ethical considerations of using AI in healthcare
Developed by industry experts, Colin Matthews, ensuring the course content is up-to-date and relevant
May require prior knowledge in deep learning or healthcare data analysis
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser