Data Science in Stratified Healthcare and Precision Medicine
Master data science techniques for healthcare. Learn sequence processing, image analysis, and machine learning for precision medicine.
Master data science techniques for healthcare. Learn sequence processing, image analysis, and machine learning for precision medicine.
This course explores the application of data science in stratified healthcare and precision medicine. Participants will gain hands-on experience working with various types of biomedical and healthcare data, including genomic data, electronic patient records, and data from wearable devices. The curriculum covers key topics such as sequence processing, image analysis, network modeling, probabilistic modeling, machine learning, natural language processing, process modeling, and graph data. Led by experts in the field, the course provides insights into successful case studies and recent advances transforming life sciences and healthcare. Suitable for those with some related experience, this intermediate-level course equips learners with the skills to leverage data science in precision medicine and stratified healthcare.
4.6
(318 ratings)
28,764 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
Powered by
What you'll learn
Understand the role of data science in stratified healthcare and precision medicine
Gain hands-on experience with Python programming for healthcare data analysis
Learn techniques for processing and analyzing genomic sequences and medical images
Explore network modeling and probabilistic approaches in biomedical research
Develop skills in applying machine learning to healthcare data
Understand natural language processing for analyzing clinical notes and medical text
Skills you'll gain
This course includes:
1 Hours PreRecorded video
6 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
Provided by
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.
There are 5 modules in this course
This course offers a comprehensive exploration of data science applications in stratified healthcare and precision medicine. Participants will learn about various types of biomedical and healthcare data, from genomic sequences to electronic patient records. The curriculum covers essential topics such as sequence processing, medical image analysis, network and probabilistic modeling, machine learning, natural language processing, and graph data. Through hands-on programming tasks and case studies, learners will gain practical skills in applying data science techniques to real-world healthcare challenges. The course also addresses societal, legal, and ethical implications of precision medicine, providing a well-rounded understanding of this rapidly evolving field.
Welcome to the Course
Module 1 · 4 Hours to complete
WELCOME TO WEEK 2
Module 2 · 2 Hours to complete
WELCOME TO WEEK 3
Module 3 · 3 Hours to complete
WELCOME TO WEEK 4
Module 4 · 2 Hours to complete
WELCOME TO WEEK 5
Module 5 · 3 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructors
Teaching and Research Fellow at the University of Edinburgh Specializing in Applied AI and Healthcare
Dr. Areti Manataki is a Teaching and Research Fellow at the Centre for Medical Informatics at the University of Edinburgh. Her research focuses on applied artificial intelligence, particularly in knowledge-based systems and healthcare applications. Areti is passionate about science communication and has extensive experience teaching introductory computer science to diverse audiences. She offers courses in both English and Spanish, including Code Yourself! An Introduction to Programming and Data Science in Stratified Healthcare and Precision Medicine. Additionally, she provides an Arabic version of her programming course titled برمج بنفسك! مقدمة حول البرمجة. Areti's work aims to bridge the gap between technology and healthcare, making complex concepts accessible to learners from various backgrounds.
Data Science MOOC Project Lead at The University of Edinburgh Specializing in Biomedical Research and Genomics
Dr. Frances Wong is the Data Science MOOC Project Lead at The University of Edinburgh. She is a biomedical research scientist with a strong focus on medical genetics, genomics, and biomedical imaging. Dr. Wong has extensive experience working with atlas-based biomedical databases and online scientific resources. She teaches the course Data Science in Stratified Healthcare and Precision Medicine, which explores the application of data science principles in the context of healthcare, emphasizing precision medicine and stratified approaches to patient care.
Testimonials
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.
4.6 course rating
318 ratings
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.