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Specialization Online

AI in Healthcare Coursera

Highlights
Tuition fee
Free
Free
Free
Unknown
Tuition fee
Free
Free
Free
Unknown
Duration
1 months
Duration
1 months
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 in Healthcare Specialization is offered by Coursera in partnership with Stanford for both healthcare providers and computer science professionals, offering insights to facilitate collaboration between the disciplines.

Overview

Artificial intelligence (AI) has transformed industries around the world, and has the potential to radically alter the field of healthcare. Imagine being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed, as well as data outside the health system -- such as social media, purchases made using credit cards, census records, Internet search activity logs that contain valuable health information, and you’ll get a sense of how AI could transform patient care and diagnoses.

In this AI in Healthcare Specialization offered by Coursera in partnership with Stanford, we'll discuss the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically.

Applied Learning Project

  • The final course will consist of a capstone project that will take you on a guided tour exploring all the concepts we have covered in the different classes. 
  • This will be a hands-on experience following a patient's journey from the lens of the data, using a unique dataset created for this specialization.
  • We will review how the different choices you make -- such as those around feature construction, the data types to use, how the model evaluation is set up and how you handle the patient timeline -- affect the care that would be recommended by the model.

Skills you'll gain

  • Machine Learning
  • Leadership and Management
  • Artificial Neural Networks
  • Data Analysis

Accreditation

The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. View the full CME accreditation information on the individual course FAQ page.

Programme Structure

Courses included:

  • Healthcare
  • Clinical Data
  • Machine Learning for Healthcare
  • Evaluations of AI Applications in Healthcare
  • AI in Healthcare Capstone

Key information

Duration

  • Part-time
    • 1 months
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online

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

Beginner Level

  • No prior experience 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
  • Domestic

    In-State
    Free

Additional Details

  • This short course is included with Coursera Plus subscription

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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