An increasing volume of data is becoming available in biomedicine and healthcare, from genomic data, to electronic patient records and data collected by wearable devices. Recent advances in data science are transforming the life sciences, leading to precision medicine and stratified healthcare.
In this course, you will learn about some of the different types of data and computational methods involved in stratified healthcare and precision medicine. You will have a hands-on experience of working with such data. And you will learn from leaders in the field about successful case studies.
Topics include: (i) Sequence Processing, (ii) Image Analysis, (iii) Network Modelling, (iv) Probabilistic Modelling, (v) Machine Learning, (vi) Natural Language Processing, (vii) Process Modelling and (viii) Graph Data.
Watch the course promo video here: http://edin.ac/2pn350P
Data Science in Stratified Healthcare and Precision Medicine
Offered By
The University of Edinburgh
About this Course
4.6
50 ratings
Skills you will gain
Data SciencePython ProgrammingMachine LearningImage Analysis
Syllabus - What you will learn from this course
Week
15 hours to complete
Welcome to the Course
Join us this week to find out how the course works and to try your hand at programming in Python!
7 videos (Total 52 min), 8 readings, 1 quiz
7 videos
About the Course2m
Demystifying Data Science4m
Python Basics Part 19m
Python Basics Part 25m
Professor Andrew Morris12m
Professor Aileen Keel15m
8 readings
Syllabus10m
Course Logistics10m
How to use the Discussion Forums10m
Course Team10m
Acknowledgements10m
Copyright10m
How to use Jupyter Notebooks10m
Programming tips & tricks10m
1 practice exercise
Quiz 120m
Week
22 hours to complete
WELCOME TO WEEK 2
This week you will be introduced to Sequence Processing and Medical Image Analysis. Explore the course materials to find out about recent advances in these areas and how they contribute to Precision Medicine!
9 videos (Total 53 min), 1 quiz
9 videos
DNA and Sequencing3m
Modelling the Data3m
Conclusion4m
Professor Tim Aitman13m
Professor David Porteous11m
Introduction1m
Medical Imaging Data & Modalities7m
Analysing Medical Images5m
1 practice exercise
Quiz 220m
Week
34 hours to complete
WELCOME TO WEEK 3
This week you will learn about Probabilistic and Network Modelling, and how they are applied to biomedicine. You will also be introduced to Machine Learning and explore the opportunities it brings to the medical field.
11 videos (Total 43 min), 1 reading, 2 quizzes
11 videos
Representing Networks3m
Biological Networks5m
Conclusion2m
Introduction2m
Statistical Methods in Medical Research4m
Conclusion3m
Introduction1m
Supervised Learning10m
Unsupervised Learning5m
Conclusion1m
1 reading
How the Programming Assignment works10m
2 practice exercises
Quiz 320m
Programming Assignment Quiz20m
Week
42 hours to complete
WELCOME TO WEEK 4
This week you will discover how clinical notes and other free-form text can be analysed with the use of Natural Language Processing techniques. You will also find out how Process Modelling can help us understand, stratify and improve healthcare processes.
9 videos (Total 57 min), 1 reading, 1 quiz
9 videos
Tasks10m
Computational Methods4m
Angus McCann from IBM7m
Introduction2m
Modelling Processes6m
Analysing Processes6m
Process Mining2m
Rodrigo Barnes from Aridhia13m
1 reading
IBM Watson10m
1 practice exercise
Quiz 420m
4.6
15 Reviews33%
started a new career after completing these courses
20%
got a tangible career benefit from this course
Top Reviews
Great course, really well designed and well produced and I feel like I've learned a lot! The coding was a bit of a shock to the system but it was nice and challenging. Thank you to the team!
One of the great course I have ever done through coursera! Thank you to Dr.Wong and Dr.Areti for their great contribution!
Instructors
Dr Areti Manataki
Teaching and Research FellowCentre for Medical Informatics
Dr Frances Wong
Data Science MOOC Project LeadCollege of Science and Engineering
About The University of Edinburgh
Influencing the world since 1583, The University of Edinburgh is consistently ranked as one of the world's top 50 universities. Today, we are an established and global leader in online learning, providing degree-level education to 3,000 online students in addition to 36,000 students on-campus. We also offer a wide range of free online courses in a variety of subjects. To find out more about studying for one of our online degrees, search for ‘Edinburgh online’ or visit www.ed.ac.uk/studying/online-learning/postgraduate
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.
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