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Coursera 4.3 (9)
Overview
Machine learning is a powerful tool for prognosis, a branch of medicine that specializes in predicting the future health of patients. In this second course, you’ll walk through multiple examples of prognostic tasks. You’ll then use decision trees to model non-linear relationships, which are commonly observed in medical data, and apply them to predicting mortality rates more accurately. Finally, you’ll learn how to handle missing data, a key real-world challenge.
These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. This AI for Medical Prognosis course offered by Coursera in partnership with Deeplearning focuses on tree-based machine learning, so a foundation in deep learning is not required for this course. However, a foundation in deep learning is highly recommended for course 1 and 3 of this specialization. You can gain a foundation in deep learning by taking the Deep Learning Specialization offered by deeplearning.ai and taught by Andrew Ng.
What you will learn
- Walk through examples of prognostic tasks
- Apply tree-based models to estimate patient survival rates
- Navigate practical challenges in medicine like missing data
Get more details
Visit programme websiteProgramme Structure
Courses include:
- Linear prognostic models
- Prognosis with Tree-based models
- Survival Models and Time
- Build a risk model using linear and tree-based models
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 2 days
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
- Self-paced
Disciplines
Artificial Intelligence Machine Learning View 268 other Short Courses in Machine Learning in United StatesExplore more key information
Visit programme websiteAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Intermediate Level
- You’re comfortable with Python programming, statistics, and probability. The Deep Learning Specialization is recommended but not required.
Make sure you meet all requirements
Visit programme websiteTuition Fee
To always see correct tuition fees
-
International
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 days. -
National
FreeTuition FeeBased on the tuition of 0 USD for the full programme during 2 days.
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Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
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