Acerca de este curso: 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
Para quién es esta clase: 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.
Creada por: The University of Edinburgh
Enseñado por: Dr Areti Manataki, Teaching and Research Fellow
Centre for Medical InformaticsEnseñado por: Dr Frances Wong, Data Science MOOC Project Lead
College of Science and Engineering
| Nivel | Intermedio |
| Compromiso | 5 weeks of study, 3-4 hours/week |
| Idioma | English |
| Cómo aprobar | Aprueba todas las tareas calificadas para completar el curso. |
| Calificaciones del usuario |
Programa
SEMANA 1
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, 8 lecturas
- Vídeo: About the Course
- Reading: Syllabus
- Reading: Course Logistics
- Reading: How to use the Discussion Forums
- Reading: Course Team
- Reading: Acknowledgements
- Reading: Copyright
- Vídeo: Demystifying Data Science
- Vídeo: Python Basics Part 1
- Reading: How to use Jupyter Notebooks
- Reading: Programming tips & tricks
- Notebook: Python Basics Part 1
- Vídeo: Python Basics Part 2
- Notebook: Python Basics Part 2
- Vídeo: Professor Andrew Morris
- Vídeo: Professor Aileen Keel
Calificado: Quiz 1
SEMANA 2
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
- Vídeo: DNA and Sequencing
- Vídeo: Modelling the Data
- Vídeo: Conclusion
- Vídeo: Professor Tim Aitman
- Vídeo: Professor David Porteous
- Vídeo: Introduction
- Vídeo: Medical Imaging Data & Modalities
- Vídeo: Analysing Medical Images
- Notebook: Image Analysis Programming Task
Calificado: Quiz 2
SEMANA 3
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, 1 lectura
- Vídeo: Representing Networks
- Vídeo: Biological Networks
- Vídeo: Conclusion
- Vídeo: Introduction
- Vídeo: Statistical Methods in Medical Research
- Vídeo: Conclusion
- Vídeo: Introduction
- Vídeo: Supervised Learning
- Vídeo: Unsupervised Learning
- Vídeo: Conclusion
- Notebook: Machine Learning Programming Task
- Reading: How the Programming Assignment works
- Notebook: Programming Assignment Notebook
Calificado: Quiz 3
Calificado: Programming Assignment Quiz
SEMANA 4
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, 1 lectura
- Vídeo: Tasks
- Vídeo: Computational Methods
- Notebook: Natural Language Processing Programming Task
- Vídeo: Angus McCann from IBM
- Reading: IBM Watson
- Vídeo: Introduction
- Vídeo: Modelling Processes
- Vídeo: Analysing Processes
- Vídeo: Process Mining
- Vídeo: Rodrigo Barnes from Aridhia
Calificado: Quiz 4
SEMANA 5
WELCOME TO WEEK 5
In this final week of the course you will learn how the Graph Data model allows for effective linkage of different data in the life sciences. You will also explore societal, legal and ethical implications of precision medicine and stratified healthcare.
7 videos, 3 lecturas
- Vídeo: Graph Data & RDF
- Vídeo: Ontologies & Graph Data Conclusion
- Reading: SPARQL Querying
- Notebook: Graph Data Programming Task
- Vídeo: Dr Steve Pavis
- Vídeo: Professor Mark Parsons
- Vídeo: Society, Law and Ethics
- Reading: General Data Protection Regulation (GDPR)
- Reading: Research Ethics
- Vídeo: Course Conclusion
Calificado: Quiz 5
Calificado: Final Course Assessment
Preguntas Frecuentes
Cómo funciona
Trabajo del curso
Cada curso es como un libro de texto interactivo, con videos pregrabados, cuestionarios y proyectos.
Ayuda de tus compañeros
Conéctate con miles de estudiantes y debate ideas y materiales del curso, y obtén ayuda para dominar los conceptos.
Certificados
Obtén reconocimiento oficial por tu trabajo y comparte tu éxito con amigos, compañeros y empleadores.
Creadores
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
Calificaciones y revisiones
One of the great course I have ever done through coursera! Thank you to Dr.Wong and Dr.Areti for their great contribution!
A good insight on healthcare perspective of data sciences.
Very insight full and packs quite the punch in terms of content
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Course introduces a varieties of Data Analytics methods and machine learning approaches for working with the stratified Healthcare data. I would recommend this course to those who are thinking about making their carrier in Data Science specially in Healthcare Business!