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Data Science in Stratified Healthcare and Precision Medicine

Dr Areti Manataki and Dr Frances Wong

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.

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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.

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What's inside

Syllabus

Welcome to the Course
Join us this week to find out how the course works and to try your hand at programming in Python!
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!
Read more

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Explores recent advances in data science for precision medicine
Uses hands-on labs
Taught by leaders in the field
Learn about real world case studies
Examines data types and computational methods for precision medicine
Provides experience in working with relevant data

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Create your own learning path. Save this course to your list so you can find it easily later.
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Reviews summary

Data science in healthcare and medicine

This course, Data Science in Stratified Healthcare and Precision Medicine, offered by The University of Edinburgh, provides an overview of applying various data science techniques to the field of biomedicine and healthcare. It covers topics ranging from sequence and image analysis to machine learning, natural language processing, and graph data, specifically within the context of precision medicine and stratified healthcare. The syllabus suggests the course aims to provide hands-on experience and explore successful case studies, alongside discussing the societal, legal, and ethical aspects of the field. Designed for learners interested in the intersection of data science and healthcare, it introduces a breadth of methods relevant to analyzing diverse data types in this domain.
Offers a basic Python programming introduction.
"Starting with Python seems helpful for learners who might need it."
"If I already know Python, the first week might be review."
"It could make the course accessible to those with some, but not extensive, programming background."
Introduces a wide range of relevant methods.
"The course structure presents a comprehensive list of data science applications."
"It looks like I will be exposed to techniques from image analysis to NLP and graph data."
"Seeing all these different methods applied in healthcare is valuable."
Discusses societal and legal implications.
"Addressing the ethical considerations is very important."
"I appreciate that they include the legal aspects of precision medicine."
"Understanding the broader societal impact is a valuable part of this field."
Includes opportunities for practical application.
"The description mentions gaining hands-on experience."
"Working with the data will be crucial for understanding the concepts."
"I expect practical exercises to reinforce the learning."
Applies data science methods to medicine.
"This course seems highly relevant for data science in healthcare."
"The specialization in stratified healthcare and precision medicine is appealing."
"It's great to see these techniques adapted specifically for biomedical data."
Large scope suggests potential for less depth.
"Covering so many topics in 5 weeks might mean less depth on each."
"I wonder if I will get a deep dive into any single method."
"It seems more like an extensive overview than a deep technical course."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Science in Stratified Healthcare and Precision Medicine with these activities:
Curate a Resource List on Open-Source Tools for Healthcare Data Analysis
Enhance your knowledge of available resources by compiling a list of open-source tools for healthcare data analysis.
Show steps
  • Research and identify various open-source tools used in healthcare data analysis
  • Organize the tools into categories based on their functionality
  • Include a brief description and links to each tool
  • Share your resource list with the class or a relevant online community
Volunteer at a local hospital or clinic
This is a great way to learn about medical research.
Show steps
  • Find a local hospital or clinic that you can volunteer at
  • Contact the volunteer coordinator and ask about opportunities
  • Sign up for a volunteer shift
Join Study Groups for Machine Learning and Healthcare Applications
Supplement your learning by engaging in peer study groups that focus on Machine Learning and its applications in healthcare.
Browse courses on Machine Learning
Show steps
  • Identify and join online or in-person study groups dedicated to Machine Learning and healthcare
  • Participate actively in discussions, ask questions, and share insights
  • Collaborate on projects or assignments related to Machine Learning in healthcare
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Improve your Python skills
Python is the language used in the course and experience using Python will make your learning experience easier.
Browse courses on Python Programming
Show steps
  • Complete a simple Python tutorial
  • Solve some coding challenges on a platform like LeetCode or HackerRank
Read 'Natural Language Processing with Python'
This book covers many of the topics covered in this course, and can be used to supplement your understanding.
View Natural Language Processing with Python:... on Amazon
Show steps
  • Read the first two chapters
  • Work through the exercises at the end of the chapters
Watch tutorials on YouTube or Coursera to learn new skills
There are many great tutorials available online that can supplement your learning.
Show steps
  • Find a tutorial on a topic that you are interested in
  • Watch the tutorial and take notes
  • Try out the skills that you learn in the tutorial
Solve Coding Challenges on Machine Learning Algorithms
Enhance your Machine Learning skills by solving coding challenges that test your understanding of various algorithms.
Browse courses on Machine Learning
Show steps
  • Join online coding platforms that offer Machine Learning challenges
  • Select challenges that cover different Machine Learning algorithms, such as supervised and unsupervised learning
  • Implement the algorithms in your preferred programming language
  • Test your code against the provided datasets and evaluate its performance
  • Analyze your results and identify areas for improvement
Further Explore Network Modelling for Medical Imaging
Deepen your understanding of Network Modelling by seeking out tutorials on its application to medical imaging.
Show steps
  • Identify relevant tutorials on Network Modelling in medical imaging
  • Watch and take notes on the tutorials, focusing on the practical applications and challenges
  • Consider enrolling in an online course or workshop on Network Modelling for medical imaging
Solve practice problems on bioinformatics websites
These problems will help you to develop your problem-solving skills and reinforce the concepts you learn in the course.
Browse courses on Bioinformatics
Show steps
  • Find a bioinformatics website with practice problems
  • Solve a few problems each day
Explore Advanced Techniques in Sequence Processing for Genomics
Expand your knowledge of Sequence Processing by seeking out tutorials on advanced techniques in genomics.
Show steps
  • Identify relevant tutorials on advanced Sequence Processing techniques for genomics
  • Watch and take notes on the tutorials, focusing on the latest algorithms and tools
  • Apply the techniques to your own genomics data or projects
Develop a Case Study on Probabilistic Modelling in Healthcare
Reinforce your grasp of Probabilistic Modelling by crafting a case study that demonstrates its use in healthcare.
Show steps
  • Identify a specific healthcare problem that can be addressed using Probabilistic Modelling
  • Gather real-world data and explore its suitability for Probabilistic Modelling
  • Apply Probabilistic Modelling techniques to analyze the data and identify patterns
  • Develop insights and recommendations based on the analysis
  • Present your case study through a written report or presentation
Create a blog post about a topic covered in the course
Explaining a concept to someone else is a great way to solidify your understanding.
Show steps
  • Choose a topic that you are comfortable with
  • Write a draft of your blog post
  • Get feedback from a friend or family member
  • Publish your blog post
Develop a Prototype Data Visualization Tool for Healthcare Data
Solidify your understanding of Data Visualization by creating a prototype tool that addresses a specific challenge in healthcare.
Browse courses on Data Visualization
Show steps
  • Identify a problem or opportunity in healthcare that can be addressed through effective data visualization
  • Design and develop the prototype using appropriate visualization techniques
  • Gather feedback from healthcare professionals and patients to refine the design
  • Present your prototype and demonstrate its potential impact
Build a machine learning model to predict a medical condition
This is a practical way to apply the skills you learn in the course.
Show steps
  • Gather data on a medical condition
  • Clean and prepare the data
  • Build a machine learning model
  • Evaluate the performance of the model

Career center

Learners who complete Data Science in Stratified Healthcare and Precision Medicine will develop knowledge and skills that may be useful to these careers:
Biomedical Data Scientist
A Biomedical Data Scientist is a computer expert that works in healthcare to help make sense of health-related data. These professionals handle a variety of projects, such as designing data pipelines, building predictive models, and developing algorithms for various applications in the medical field. Since the field of healthcare collects a significant amount of data, this course may be helpful for you to get started in this field.
See salaries and explore the career path for Biomedical Data Scientist
Data Architect
A Data Architect is responsible for designing, building, and maintaining data systems. They work with business stakeholders, data analysts, and other IT professionals to ensure that data systems meet the needs of the organization. This course may be helpful for you if you are interested in a career as a Data Architect, as it covers a variety of topics that are relevant to the field, such as data modeling and data integration.
See salaries and explore the career path for Data Architect
Data Scientist
A Data Scientist is responsible for collecting, analyzing, and interpreting data to find patterns and trends. They work with a variety of stakeholders to make recommendations and develop solutions. This course may be helpful for you if you are interested in a career as a Data Scientist, as it covers a variety of topics that are relevant to the field, such as data mining and data visualization.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
A Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models. They work with data scientists, software engineers, and other professionals to develop solutions to complex problems. This course may be helpful for you if you're interested in a career as a Machine Learning Engineer, as it covers a variety of topics that are relevant to the field, such as machine learning and natural language processing.
See salaries and explore the career path for Machine Learning Engineer
Software Engineer
A Software Engineer is responsible for designing, developing, and maintaining software applications. They work with a variety of stakeholders to ensure that software applications meet the needs of the organization. This course may be helpful for you if you are interested in a career as a Software Engineer, as it covers a variety of topics that are relevant to the field, such as software design and software testing.
See salaries and explore the career path for Software Engineer
Biostatistician
A Biostatistician designs studies, collects and analyzes data, and interprets results for use in making medical decisions. They can work in a variety of settings and may collaborate with scientists, researchers, and healthcare providers. Since this field involves the use of data science to make better decisions, this course may offer you an advantage by exposing you to different topics related to data analysis and data processing that are used in this field.
See salaries and explore the career path for Biostatistician
Healthcare Data Analyst
A Healthcare Data Analyst is responsible for collecting, analyzing, and interpreting healthcare data to improve patient care. They work with healthcare providers, administrators, and researchers to identify trends, develop solutions, and improve the quality of care. This course may be useful for you to get started as it covers a variety of topics that are relevant to this field, such as natural language processing and machine learning.
See salaries and explore the career path for Healthcare Data Analyst
Clinical Data Manager
A Clinical Data Manager is in charge of planning, monitoring, and analyzing data for clinical trials. They ensure that data is accurate, complete, and reliable, and they prepare reports and presentations to communicate findings. If you are interested in working in clinical research, then this course may be helpful to you as it covers a variety of different data types and computational methods that are used in the field.
See salaries and explore the career path for Clinical Data Manager
Health Informatics Specialist
A Health Informatics Specialist is responsible for managing and analyzing health data. They work with a variety of stakeholders to ensure that health data is accurate, complete, and reliable. This course may be helpful for you if you are interested in a career as a Health Informatics Specialist, as it covers a variety of topics that are relevant to the field, such as data mining and data visualization.
See salaries and explore the career path for Health Informatics Specialist
Biomedical Engineer
A Biomedical Engineer is responsible for designing and developing medical devices and technologies. They work with a variety of stakeholders to ensure that medical devices and technologies are safe and effective. This course may be helpful for you if you are interested in a career as a Biomedical Engineer, as it covers a variety of topics that are relevant to the field, such as medical imaging and medical device design.
See salaries and explore the career path for Biomedical Engineer
Medical Physicist
A Medical Physicist is a scientist who uses physics principles to work in the medical field. They use their skills to provide healthcare professionals with the technology and knowledge they need to diagnose and treat patients. As a Medical Physicist, you could work in a hospital, clinic, research lab, or teach at a university. The topics covered by this course, such as sequence processing and image analysis, may be useful for learning about the different types of data and computational methods that are involved in the field.
See salaries and explore the career path for Medical Physicist
Clinical Research Associate
A Clinical Research Associate is responsible for managing clinical trials. They work with a variety of stakeholders to ensure that clinical trials are conducted in accordance with good clinical practice guidelines. This course may be helpful for you if you are interested in a career as a Clinical Research Associate, as it covers a variety of topics that are relevant to the field, such as clinical trial design and clinical trial management.
See salaries and explore the career path for Clinical Research Associate
Healthcare Administrator
A Healthcare Administrator is responsible for managing the day-to-day operations of a healthcare organization. They work with a variety of stakeholders to ensure that the organization is running smoothly and efficiently. This course may be helpful for you if you are interested in a career as a Healthcare Administrator, as it covers a variety of topics that are relevant to the field, such as healthcare finance and healthcare management.
See salaries and explore the career path for Healthcare Administrator
Healthcare Consultant
A Healthcare Consultant is responsible for providing advice and guidance to healthcare organizations on how to improve their operations. They work with a variety of stakeholders to identify and solve problems, and they develop and implement solutions. This course may be helpful for you if you are interested in a career as a Healthcare Consultant, as it covers a variety of topics that are relevant to the field, such as healthcare finance and healthcare policy.
See salaries and explore the career path for Healthcare Consultant
Medical Writer
A Medical Writer is responsible for writing and editing medical documents, such as patient education materials, clinical trial protocols, and scientific articles. They work with a variety of stakeholders to ensure that medical documents are accurate, clear, and concise. This course may be helpful for you if you are interested in a career as a Medical Writer, as it covers a variety of topics that are relevant to the field, such as medical terminology and scientific writing.
See salaries and explore the career path for Medical Writer

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Science in Stratified Healthcare and Precision Medicine.
Cover image
Introduction to Bioinformatics
Save
Provides a comprehensive overview of bioinformatics, including sequence analysis, gene expression analysis, and protein structure prediction.
Introduction to Bioinformatics
Paperback
$$$
Introduction to Bioinformatics
Paperback
$$$
Introduction to Bioinformatics
Paperback
$$
Cover image
Bioinformatics Data Skills
Save
Covers data management, analysis, and visualization techniques essential for bioinformatics research.
Bioinformatics Data Skills: Reproducible and Robust...
Paperback
$$
Bioinformatics Data Skills: Reproducible and Robust...
Kindle Edition
$$
Cover image
Machine Learning for Healthcare Systems
Save
Provides an introduction to machine learning algorithms and their applications in healthcare, including disease diagnosis, patient risk assessment, and treatment selection.
Machine Learning for Healthcare Systems:...
Kindle Edition
$$$$
Biomedical Informatics
Save
Provides a comprehensive overview of biomedical informatics, including its history, applications, and ethical and societal implications.
Biomedical Informatics
Paperback
Check
Biomedical Informatics
Kindle Edition
Check
Cover image
Health Informatics: Practical Guide Seventh Edition
Save
Provides practical guidance on the use of health informatics in healthcare settings, including data management, analytics, and interoperability.
Health Informatics: Practical Guide, Seventh Edition
Kindle Edition
$$
Health Informatics: Practical Guide Seventh Edition
Paperback
$$
Cover image
Data Science for Healthcare
Save
Provides a practical guide to using data science in healthcare, including case studies and examples.
Data Science for Healthcare: Methodologies and...
Kindle Edition
$$$$

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Course image
Effort
5 weeks of study, 3-4 hours/week
Level
Intermediate
Via
Coursera
Institution
The University of Edinburgh
Instructors
Dr Areti Manataki
Dr Frances Wong
Language
English
Transcripts
Español Français Português Deutsch Italiano 中文 العربية 한국어 日本語 हिंदी Nederlands Svenska Pусский Türkçe Polski Ελληνικά українська мова magyar nyelv Bahasa Indonesia ไทย қазақша اُردُو, فارسی বাংলা tiếng Việt پښتو آذربایجان دیلی
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Explores recent advances in data science for precision medicine
Uses hands-on labs
Taught by leaders in the field
Learn about real world case studies
Examines data types and computational methods for precision medicine
Provides experience in working with relevant data
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