About this course: 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
Who is this class for: This course is aimed at learners who are familiar with the basic principles of biomedical and healthcare practice, and who have an interest in data science. Prior knowledge in computer programming or data science is not needed.
Taught by: Dr Areti Manataki, Teaching and Research Fellow
Centre for Medical Informatics
Taught by: Dr Frances Wong, Data Science MOOC Project Lead
College of Science and Engineering
| Level | Intermediate |
| Commitment | 5 weeks of study, 3-4 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
- Video: About the Course
- Leyendo: Syllabus
- Leyendo: Course Logistics
- Leyendo: How to use the Discussion Forums
- Leyendo: Course Team
- Leyendo: Acknowledgements
- Leyendo: Copyright
- Video: Demystifying Data Science
- Video: Python Basics Part 1
- Leyendo: How to use Jupyter Notebooks
- Leyendo: Programming tips & tricks
- Libreta: Python Basics Part 1
- Video: Python Basics Part 2
- Libreta: Python Basics Part 2
- Video: Professor Andrew Morris
- Video: Professor Aileen Keel
- Video: DNA and Sequencing
- Video: Modelling the Data
- Video: Conclusion
- Video: Professor Tim Aitman
- Video: Professor David Porteous
- Video: Introduction
- Video: Medical Imaging Data & Modalities
- Video: Analysing Medical Images
- Libreta: Image Analysis Programming Task
- Video: Representing Networks
- Video: Biological Networks
- Video: Conclusion
- Video: Introduction
- Video: Statistical Methods in Medical Research
- Video: Conclusion
- Video: Introduction
- Video: Supervised Learning
- Video: Unsupervised Learning
- Video: Conclusion
- Libreta: Machine Learning Programming Task
- Leyendo: How the Programming Assignment works
- Libreta: Programming Assignment Notebook
- Video: Tasks
- Video: Computational Methods
- Libreta: Natural Language Processing Programming Task
- Video: Angus McCann from IBM
- Leyendo: IBM Watson
- Video: Introduction
- Video: Modelling Processes
- Video: Analysing Processes
- Video: Process Mining
- Video: Rodrigo Barnes from Aridhia
- Video: Graph Data & RDF
- Video: Ontologies & Graph Data Conclusion
- Leyendo: SPARQL Querying
- Libreta: Graph Data Programming Task
- Video: Dr Steve Pavis
- Video: Professor Mark Parsons
- Video: Society, Law and Ethics
- Leyendo: General Data Protection Regulation (GDPR)
- Leyendo: Research Ethics
- Video: Course Conclusion
Cada curso es como un libro de texto interactivo, con videos pregrabados, cuestionarios y proyectos.
Conéctate con miles de estudiantes y debate ideas y materiales del curso, y obtén ayuda para dominar los conceptos.
Obtén reconocimiento oficial por tu trabajo y comparte tu éxito con amigos, compañeros y empleadores.
Very insight full and packs quite the punch in terms of content
The course fulfills all my expectations, I'm looking forward to enrolling in a further version of it.
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!
RA
A good insight on healthcare perspective of data sciences.