Courses / Research Software Engineering
Research Software Engineering
Research software engineering is crucial in health data research because it helps ensure that the software used to analyse and interpret health data is reliable, robust, and accurate. In health data research, software plays a critical role in analysing and interpreting large, complex and sensitive data sets. The software used in health data research must be able to handle vast amounts of data, perform complex computations, and produce results that are both accurate and trustworthy.
This course is designed to provide you with an understanding of software engineering practices and principles that are particularly relevant to the research community.
You will learn about various software development methodologies, tools, and techniques that are commonly used in research software engineering. You will also learn about best practices for software design, coding, testing, and documentation, and how to apply these principles to your own software projects. Furthermore, you will be introduced to the key challenges and considerations that are unique to the research software engineering domain, such as ensuring reproducibility and collaboration, and balancing the trade-offs between performance and code maintainability.
By the end of this course, you will have a solid introduction to research software engineering and the skills you need to develop high-quality, reliable software for your research projects.
This course is for aspiring and practising research software engineers in health data research.
Introduction
Welcome to 'Research Software Engineering'
Your Instructors
Course
Publishing code and software (6:16)
How to create modular software (6:28)
Reproducible analytical pipelines webinar (49:14)
Introduction to reproducible analysis pipelines (8:32)
Working towards reproducible research practices (11:26)
Reproducible code (11:31)
Reproducible data analysis (23:53)
Introduction to version control for code (6:50)
An introduction to developing software tools and packages in health data research (13:17)
Managing collaborative coding projects (14:10)
Using Conda for reproducible research (08:33)
Coding with style (05:22)
Continuous integration/delivery (4:14)
Using containers to stabilise the computing environment (5:57)
Docker webinar series
Session 1: Using Docker containers reproducibly in multiple computing environments (48:59)
Session 2: Building and modifying containers for reproducible research (48:30)
Session 3: Roundtable discussion on phenotype mining and aggregation (58:53)
Quiz
Quiz (10 Questions)
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