MSc/PGDip/PGCert Health Informatics (UCL/UoM Joint Award)

Year of entry: 2022

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Course unit details:
Modern Information Engineering

Unit code IIDS61301
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Offered by Division of Informatics, Imaging and Data Sciences
Available as a free choice unit? No


This module builds on the local support for Software Carpentry ( ) at UoM and UCL to provide an opportunity for trainees who seek to understand and make appropriate use of modern programming skills and data management technologies. It will provide some hands-on experience in software design, implementation and data retrieval. Trainees are taught best practice for creating useful and effective software solutions to real-world health problems as well as discussing modern data management technologies such as virtualisation and cloud. During the module trainees will be asked to work in teams to implement a bespoke system for a clinical team. Trainees are taught the fundamentals of programming on the module, and do not need to have had any prior programming experience.


The unit aims to introduce students to a hands-on experience of modern information engineering skills including basic programming skills using Python; automation of tasks, how track work for efficiently; and how to store and manage data effectively as well as access it using SQL.

Learning outcomes


Category of outcome

Students should be able to:

A. Knowledge and understanding

LO1: Use core programming concepts to design and implement software

LO2: Critical understanding of  data management technologies (including their strengths and limitations) for use in real-world settings

LO3: Apply and critically appraise the software design process to a range of case-study projects

LO4:   Understand be able to select APIs to allow systems to communicate with each other

LO5: database systems/data management and modern software processes contribute to patient care pathways and the provision of high quality safe and effective patient care

LO6:  Develop plans of how to apply software quality assurance processes to a range of case-studies

LO7: Demonstrate the importance of  key role of version control systems in quality assurance

B. Intellectual skills

LO8: Plan a process for a clinical information system

LO9: Critically appraise a software design process

C. Practical skills

LO10: Develop a system for a clinical team

LO11: Construct a range of SQL commands to extract data from management systems

LO12: Complete project documentation ensuring compliance with security, governance and ethics issues with web-based systems

LO13: Design a relational database to solve a real-world scenario

LO14: Write programs in a language (e.g., python) to manipulate data

D. Transferable skills and personal qualities

LO15: Work collaboratively within a team

LO16: Communicate effectively both in written and verbal format to both non-technical and technical audiences:

LO17: Work through the problem-solving cycle



Teaching and learning methods

This unit will delivered in a blended format: e-Learning preparation material will impart basic and core knowledge whilst the face-to-face lectures and open discussions will introduce concrete examples and encourage attendees to draw upon their own reading and experience.  Group, problem based learning will show a deeper understanding of the area and encourage collaborative working.  Example case-studies will be drawn from University of Manchester (HeRC) and University College London research-driven projects and current NHS projects.  The F2F teaching will be delivered as 1 x three day block of workshops covering a key section

Assessment methods



Assessment task



Weighting in unit




Working in groups, the assessment will be split into 3 iterations that all add up to 70%. The small groups will develop a common understanding of the problem and then to work as a part of a team to design and implement software.










 Software practices


The assessment will involve the cohort working in small groups to develop a common understanding of the problem and then to work as a part of a team to implement software.




 Reflective blog

Experiences of collaborative software development

500 words



Feedback methods

Formative assessment and feedback to students is a key feature of the on-line learning materials for this unit. 

Regular presentation of results to tutor and staff to elicit feedback and develop ideas/work.

Recommended reading

There are lots of examples of practical computing books for non-computer scientists.  Papers to include for this teaching include:

John D. Blischak, Emily R. Davenport, and Greg Wilson: "A Quick Introduction to Version Control with Git and GitHub" PLoS Computational Biology, 2016

Matthew Gentzkow and Jesse Shapiro: "Code and Data for the Social Sciences: A Practitioner's Guide.", 2014.

Jo Erskine Hannay, Hans Petter Langtangen, Carolyn MacLeod, Dietmar Pfahl, Janice Singer, and Greg Wilson: "How Do Scientists Develop and Use Scientific Software?Proc. 2009 ICSE Workshop on Software Engineering for Computational Science and Engineering, 2009.

Edmund Hart, Pauline Barmby, David LeBauer, François Michonneau, Sarah Mount, Timothée Poisot, Kara H. Woo, Naupaka Zimmerman, and Jeffrey W Hollister: "Ten Simple Rules for Digital Data StoragePeerJ PrePrints, 2015.

Ethan P. White, Elita Baldridge, Zachary T. Brym, Kenneth J. Locey, Daniel J. McGlinn, and Sarah R. Supp: "Nine Simple Ways to Make It Easier to (Re)use Your DataPeerJ PrePrints, 2013.

Greg Wilson, D. A. Aruliah, C. Titus Brown, Neil P. Chue Hong, Matt Davis, Richard T. Guy, Steven H. D. Haddock, Kathryn D. Huff, Ian M. Mitchell, Mark D. Plumbley, Ben Waugh, Ethan P. White, and Paul Wilson: "Best Practices for Scientific ComputingPLoS Biology, 2014.

Study hours

Independent study hours
Independent study 150

Teaching staff

Staff member Role
Alan Davies Unit coordinator

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