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
ofrecido por
The University of Edinburgh
Acerca de este Curso
4.7
31 calificaciones
Habilidades que obtendrás
Data SciencePython ProgrammingMachine LearningImage Analysis
Programa - Qué aprenderás en este curso
Semana
1Welcome 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 minutos), 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 lecturas
Syllabus10m
Course Logistics10m
How to use the Discussion Forums10m
Course Team10m
Acknowledgements10m
Copyright10m
How to use Jupyter Notebooks10m
Programming tips & tricks10m
1 ejercicio de práctica
Quiz 120m
Semana
2WELCOME 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 minutos), 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 ejercicio de práctica
Quiz 220m
Semana
3WELCOME 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 minutos), 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 lectura
How the Programming Assignment works10m
2 ejercicios de práctica
Quiz 320m
Programming Assignment Quiz20m
Semana
4WELCOME 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 minutos), 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 lectura
IBM Watson10m
1 ejercicio de práctica
Quiz 420m
Principales revisiones
por SW•Jun 8th 2018
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!
por SJ•Sep 1st 2018
One of the great course I have ever done through coursera! Thank you to Dr.Wong and Dr.Areti for their great contribution!
Instructores
Dr Areti Manataki
Teaching and Research FellowCentre for Medical Informatics
Dr Frances Wong
Data Science MOOC Project LeadCollege of Science and Engineering
Acerca de 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
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si compro el Certificado?
Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.
¿Cuál es la política de reembolsos?
¿Hay ayuda económica disponible?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.
Coursera brinda acceso universal a la mejor educación del mundo, al asociarse con las mejores universidades y organizaciones, para ofrecer cursos en línea.
© 2018 Coursera Inc. Todos los derechos reservados.
