Introduction to Data Science for Healthcare Professionals
Explore the possibilities, concepts, and requirements of working with or alongside big data in the healthcare sector.
323 enrolled on this course
Duration
4 weeksWeekly study
2 hours100% online
How it works
Introduction to Data Science for Healthcare Professionals
Discover data analysis concepts and their applications in healthcare with KCL
Data has had transformative effects on healthcare delivery and management, though many professionals in the sector remain unfamiliar with how to gather and interpret data.
On this six-week course from King’s College London, you’ll explore data science concepts, focusing on how data is collected, analysed, and used to inform professional practice in the healthcare sector.
Examine the data science process, including data modelling, analysis, and visualisation
Data science can help answer questions and explore new perspectives.
You’ll be introduced to data science techniques and systems, defining key terms and concepts, before investigating core skills used in data analysis, modelling, and visualisation.
You’ll also gain an overview of the ethical considerations required when handling data in healthcare, and identify some of the risks and challenges of big data analysis.
With this knowledge, you’ll be able to demonstrate how data can be captured, manipulated, and interpreted for meaningful answers in healthcare contexts.
Work effectively with data scientists and data teams
Having examined the terminology and processes used in data science, you’ll identify opportunities for collaboration with data scientists and teams, improving communication and understanding.
You’ll also be able to explain how your own role may interface with data scientists and data teams.
Understand the role of a data management system in storing and structuring data
You’ll learn how data management systems can organise large amounts of data in an easy to access repository and how this can help optimise data use across departments.
By the end of this course, you’ll have gained an overview of data science processes in healthcare contexts, kickstarting your upskilling in a valuable and necessary area.
Syllabus
Week 1
Defining Data Science
Welcome to Data Science in Healthcare
This activity will set the scene for what you are going to learn over the next four weeks. We will introduce the course, who developed and help you learn why data science will be important in your healthcare role.
What is Data Science
We will define data science terms, techniques and systems. This will help you start to recognise the language used in data science teams.
The data science team
There are various roles within the world of data science in healthcare. Let's explore some of them here.
Developing questions to ask the data
How do you develop and effectively word the questions you are asking and trying to answer with the data?
Wrap up and summary of week one
Lets recap what we have learnt in week one and see what we cover in week 2
Week 2
What we can do with all the data available
Where this data can be used in healthcare.
This a summary of the weeks learning and lets listen to some examples of where access to all this data might be helpful in healthcare.
Data Basics
Get to know your data and how to store and structure your data.
Data Management
Effective data management is key to the data analysis pipeline. It is also a task which one is trusted with patients and the public data so being able to use it in best way is important.
Summary of the week
Lets recap the learning objectives of the week.
Week 3
Sharing the results of our data
Introduction to the week
Lets go over what we learn this week, as we start to look data analysis and visualization
Introduction to Data Analysis
Now that you have enough data, which is stored in the best location and is in a format that is easy to use you can start to analyse it.
Data Analysis Tools and Skills
Lets look at some of the tools used in data analysis and where to find more training
Data Visualisation
As we have touched being able to share and communicate your results is a key step in the data analysis pipeline. Lets look into this in more detail.
Wrap up and summary of week three
Lets go over what we have learned this week and see what is to come in week four.
Week 4
Applying data science in healthcare
Overview of week four
Lets see what we will be covering in this final week of the course.
Data protection - GDPR
Health and clinical data is sensitive data so understanding the legislation the governs its use is important.
Ethics of Data Science and AI
Here we will cover some of the risks that come with working with Big data and highlight some ethical concerns of Artificial Intelligence. This will give us a chance to explore the ways these challenges can be mitigated.
Case studies
Lets look at three case studies from various aspects of healthcare to see where the use of data science has made a real impact to care, service provision and research.
Wrap up and connect
Lets review the last week and the whole course.
When would you like to start?
Start straight away and join a global classroom of learners. If the course hasn’t started yet you’ll see the future date listed below.
Available now
Learning on this course
On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- Explore the common data science techniques and systems and to be able to give clear definitions of them
- Apply your understanding of data science terms when communicating with data scientists or teams working with data to collaborate effectively
- Identify where your role may interface within a data science team
- Develop and effectively word the research question they are trying to answer with their data
- Identify various data management systems that they may use to store and structure their data
- Identify the various data analysis techniques you could apply to your data to best answer your question
- Explore the process of data cleaning required prior to analysing data
- Describe any further training opportunities that would support you in developing your data science knowledge to apply to health care
- Understand the importance of data visualization and be able to recognise its value in being able to share data between the analyst, the data expert and patients and public.
- Critique the risks of using AI and Big Data and the perception this has from patients and public.
- Identify best practice when using AI and Big Data to minimize risks including understanding the current legislation in place.
Who is the course for?
This course is designed for healthcare professionals with no experience in data science but whose job roles require them to work alongside or lead teams dealing with data science.
It’s suitable for professionals working in both clinical and non-clinical roles including scientists, management, clinicians, nurses, and pharmacists who have access to and manage data projects or large amounts of data.
Who will you learn with?
Who developed the course?
King's College London
King’s College London, established in 1829 and a founding college of the University of London, is one of the world’s leading research and teaching universities, based in the very heart of London.
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| Choose the best way to learn for you! | $134/one-off payment | $349.99 for one year Automatically renews | Free |
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| Access to this course | tick | tick | Access expires 25 May 2024 |
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| Learn at your own pace | tick | tick | cross |
| Discuss your learning in comments | tick | tick | tick |
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Cancel for free anytime |
Ways to learn
Choose the best way to learn for you!
Subscribe & save
$349.99 for one year
Automatically renews
Develop skills to further your career
- Access to this course
- Access to 1,000+ courses
- Learn at your own pace
- Discuss your learning in comments
- Digital certificate when you're eligible
Cancel for free anytime
Buy this course
$134/one-off payment
Fulfill your current learning need
- Access to this course
- Learn at your own pace
- Discuss your learning in comments
- Printed and digital certificate when you’re eligible
Limited access
Free
Sample the course materials
- Access expires 25 May 2024
Find out more about certificates, Unlimited or buying a course (Upgrades) | |||
Find out more about certificates, Unlimited or buying a course (Upgrades)
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