Introduction to Data Health Science
Advance your career by mastering health data science tools, including R and SQL, to solve healthcare challenges.
Cost
£1,290
Transform healthcare and data health science with the University of Aberdeen
Health data scientists play a critical role in healthcare by using their expertise to analyse complex data and extract valuable insights. Their work supports decision-making processes in clinical settings, improves patient outcomes, and optimises operational efficiencies.
By leveraging statistical analysis, machine learning, and data visualisation techniques, they contribute significantly to the development and implementation of data-driven strategies in healthcare.
Understand the role of Health Data Scientists in Healthcare
The healthcare industry relies on health data scientists to analyse complex data and extract valuable insights to improve decision-making in clinical settings, patient outcomes, and operational efficiencies.
Take the first steps into this critical field with this online microcredential from the University of Aberdeen. You'll learn to harness the power of data to address healthcare challenges and grow your career with impact.
Under the guidance of industry experts and supportive faculty, you'll walk away with the tools to innovate and drive the future of healthcare forward.
Understand the role of Health Data Scientists in Healthcare
By leveraging statistical analysis, machine learning, and data visualisation techniques, they contribute significantly to the development and implementation of data-driven strategies in healthcare.
Master the use of SQL for health data extraction
SQL (Structured Query Language) helps health data scientists efficiently manage and manipulate large datasets.
You’ll learn more about this essential tool and how you can use it to extract relevant data from various databases, perform complex queries, and generate reports that support clinical and administrative decision-making.
With this expertise, you’ll also learn to filter and aggregate data to identify patterns and trends, which are crucial for improving patient care.
Clean, explore, and visualise data with R programming
As a data scientist professional, you'll need to know how to clean and visualise data to ensure analyses are not only done with reliable information but findings are communicated effectively.
To help you develop these skills, you'll explore R programming. Once you understand the fundamentals of this tool, you'll explore more of its functions, such as preprocessing data, uncovering data patterns, and creating sophisticated visualisations that make complex data more accessible.
Explore ethical and legal issues in health data research
A fundamental part of working with data is knowing how to handle it ethically. This microcredential will factor the ethical considerations, especially when working with health-specific data. You’ll consider how to obtain informed consent, ensure data anonymity, and maintain transparency with research subjects.
The role of health data scientists in healthcare is multifaceted and vital for the industry's advancement. From mastering SQL for data extraction to cleaning and visualising data with R programming, their skills directly impact the quality of patient care and operational efficiencies.
How will the skills you learn help in your career?
By the end of this course, you’ll have accumulated a range of knowledge that can be immediately applied to real-world healthcare scenarios.
You’ll have mastered the process of collecting, managing, and analysing health data using tools, including R and SQL, and understood the art of visualising and communicating health data effectively.
Not only that, but you’ll gain a solid understanding of the ethical, legal, and technical challenges in health data science.
With this comprehensive foundation, you’ll be well-prepared to tackle healthcare problems, work towards a career as a health data scientist or analyst, and take more advanced courses to further your professional development.
How will you be assessed?
On this microcredential, you’ll be assessed through a combination of assignments, practical projects, and exams. These methods are designed to evaluate your understanding of health data science concepts, your ability to apply R programming and SQL for data analysis, and your skills in communicating findings effectively.
Each module may include quizzes to test your knowledge and one-to-one online tutorials to support your learning progress. Your final grade will reflect your performance across these diverse assessment methods.
What will you receive?
Upon completing this microcredential, you’ll receive 15 Master’s level credits from the University of Aberdeen, which you can use towards a Master's in Applied Health Sciences or a Master's in Data Science
How long is this microcredential?
This part-time microcredential is 12 weeks long, totalling approximately 150 hours of study and assessment time. This course is fully flexible, meaning you can set your study hours each week and work through modules at your own pace.
It’s recommended you devote 10-15 hours per week to stay on track.
Are you eligible for this microcredential?
There are no formal entry requirements to join this master’s-level microcredential, simply an interest in the subject matter and a good grasp of the English language.
While you don’t need to provide proof of your English language level before the start, an IELTS score of 6.5 overall is recommended to complete the course.
Is this microcredential right for you?
This online microcredential is an ideal first step for anyone interested in building their skills in health data science, including SQL for data extraction, R programming for data cleaning and visualisation, and understanding ethical and legal issues in health data research.
If you're thinking about growing your career as a health data scientist or exploring opportunities within healthcare organisations, government health agencies, or the pharmaceutical industry, this microcredential is for you.
Syllabus
What happens before, during, and after your microcredential
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