MSc ACS: Digital Biology
Year of entry: 2023
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Course unit details:
|Unit level||FHEQ level 7 – master's degree or fourth year of an integrated master's degree|
|Teaching period(s)||Semester 1|
|Available as a free choice unit?||Yes|
This module will examine the entire data life cycle, including data creation, modelling, acquisition, representation, use, maintenance, preservation and disposal. As the majority of data is stored in databases, the module will examine various database engineering approaches to support data management, including database design, data warehousing, maintenance and analytics. Data standards and data quality will be examined and the challenge of "big datasets" will be considered.
Explain and apply the constituent steps of the data life cycle
Describe data engineering techniques; be able to apply and document large-scale data engineering for a given task, comprising various multimodal data types.
Describe and apply technical, ethical and societal issues related to data engineering, storage, access and maintenance.
Explain and apply the main principles of data analytics/ algorithms, and explain their application to various domains.
Describe relevant standards and best practice in data engineering, analyse shortcomings and identify possible strategies and approaches to overcome them.
- An overview of the data life cycle
- Data engineering, modelling and design techniques
- Data storage and warehousing
- Data access and maintenance
- Data analytics application and algorithms
- Engineering non-traditional data types
- Data standards and data quality
- Analytical skills
- Problem solving
- Written communication
|Written assignment (inc essay)||100%|
|Scheduled activity hours|
|Practical classes & workshops||20|
|Independent study hours|
|Sandra Sampaio||Unit coordinator|