Fundamentals of Machine Learning for Healthcare It's a Free Course. Enroll it before the instructor makes it to the paid course.
What you will learn from the Fundamentals of Machine Learning for Healthcare
- Learn about advanced neural network architectures for tasks ranging from text classification to object detection and segmentation
- Learn important approaches for leveraging data to train, validate, and test machine learning models
- Understand how dynamic medical practice and discontinuous timelines impact clinical machine learning application development and deployment
- Supervised Machine Learning Approaches
- Traditional Supervised Machine Learning Approaches
- Deep Learning and Neural Networks
- Representing Unstructured Image and Text Data
- Natural Language Processing and Recurrent Neural Networks
- Convolutional Neural Networks
- Advanced Neural Network Architectures
- Statistical Approaches to Model Evaluation
- Common Clinical Machine Learning Challenges
- Medical Data Challenges in Machine Learning
- Building Multidiciplinary Teams for Clinical Machine Learning
Course Instructors Matthew Lungren, Serena Yeung & Offered by Stanford University from Coursera
Course Duration: 12 hours to complete
Course is for Beginner Level
Can I download Fundamentals of Machine Learning for Healthcare course?
Course videos can be downloaded for offline viewing using the Udemy mobile app on Android and iOS. Some courses may allow downloading lectures on a computer only if the instructor has enabled it, but this is not guaranteed and is not the primary method Udemy supports.Can I get a certificate after completing the course?
Yes. After successful completion of the Fundamentals of Machine Learning for Healthcare, learners will receive a certificate of completion. The certificate confirms that the course has been completed and can be downloaded and shared on resumes or professional profiles.Are there any other coupons available for this course?
Additional coupons for this course may be available from time to time. Coupon availability is time-limited and may change or expire at any time, so it’s recommended to check regularly for updated offers.Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
