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AI for Medical Prognosis Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
21 days
Duration
21 days
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

This AI for Medical Prognosis course offered by Coursera in partnership with Deeplearning will give you practical experience in applying machine learning to concrete problems in medicine.

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  

Programme 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

Key information

Duration

  • Part-time
    • 21 days
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic 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.

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

Audit: free access to course materials except graded items|Certificate: a trusted way to showcase your skills|A year of unlimited access with Coursera Plus $199

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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