RiseUpp Logo
RiseUpp Logo
Health Data Science Foundation
Educator Logo

Powered by

Provider Logo

Completion

CERTIFICATE

Health Data Science Foundation

Develop expertise in machine learning and deep learning algorithms for healthcare applications, including medical data analysis and predictive modeling.

Course Cost

Free course

Advanced

Skill Level

22 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Deep Learning for Healthcare Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.6

4,069 Enrolled

English

Powered by

Provider Logo

4.6

4,069 Enrolled

English

What you'll learn

  • Process and analyze different types of healthcare data

  • Implement machine learning models for medical applications

  • Understand healthcare data standards and their applications

  • Develop deep neural networks for healthcare problems

  • Apply predictive modeling in medical scenarios

Skills you'll gain

Health Data Analysis
Machine Learning
Deep Learning
Neural Networks
Healthcare Informatics
Data Processing
Medical Data Standards
Predictive Modeling
Unsupervised Learning
Feature Engineering

This course includes:

3.7 Hours PreRecorded video

4 quizzes, 4 programming assignments

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Closed caption

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

CREATED BY

Educator Logo

PROVIDED BY

Provider Logo
Certificate
Certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

CREATED BY

Educator Logo

PROVIDED BY

Provider Logo

Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

icon-0icon-1icon-2icon-3icon-4

There are 4 modules in this course

This comprehensive course bridges machine learning and healthcare, focusing on the foundational aspects of health data science. Students learn about various types of healthcare data, including electronic health records, medical imaging, and clinical notes, along with relevant data standards. The curriculum covers essential machine learning concepts, from feature construction to deep neural networks, with practical applications in healthcare scenarios. Through hands-on programming assignments and real-world examples, participants develop skills in processing and analyzing healthcare data using modern machine learning techniques.

Introduction

Module 1 · 5 Hours to complete

Health Data

Module 2 · 6 Hours to complete

Machine Learning Basics

Module 3 · 6 Hours to complete

Deep Neural Networks (DNN)

Module 4 · 5 Hours to complete

Fee Structure

Reviews

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Health Data Science Foundation

Advanced

Skill Level

22 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.