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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2022/2023

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DRPS : Course Catalogue : School of Engineering : Postgrad (School of Engineering)

Postgraduate Course: Data Science for Decision Makers (MSc) (PGEE11201)

Course Outline
SchoolSchool of Engineering CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits10 ECTS Credits5
SummaryThis course introduces key concepts and ideas from data science and data management and looks at how these relate to decision making processes in organisations. It is aimed at those with a less technical background, but with experience in project management. The course is designed to be incorporated into the Leading Major Programme and will be delivered in part by partners from EPCC (University of Edinburgh) and from industry.
Course description The course will cover:
- Definitions of 'Data Science', 'Big Data' and related terms
- Questions that data can address
- Data lifecycles & data management planning
- Data analysis processes
- Where data is stored (e.g. files, relational databases, NoSQL databases)
- How data is stored (e.g. file formats)
- Types of data science tools, libraries (incl. workbooks)
- Basic machine learning: supervised vs unsupervised learning
- Processing data: cluster vs cloud vs high performance computing
- Ethical & legal considerations for data
- The role of data in a digital strategy
- How data science fits with existing processes and infrastructure
- Data science organisational roles
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. Explain important concepts relating to data science and its relationship to decision making;
  2. Identify and specify relevant roles for a data science team, understanding what could be expected in each role;
  3. Identify potential data science approaches to business problems and recognise factors which might affect their suitability;
  4. Communicate with a data science team and discuss the relationship between business questions and relevant data science techniques;
  5. Incorporate data-driven decision-making processes into a wider digital strategy.
Reading List
- C. O'Neil and R. Schutt, Doing Data Science: Straight Talk from the Frontline, O'Reilly Media (2013), ISBN: 978-1449358655
- A number of videos (from related UoE courses) will also be provided to the students in advance of the face-to-face teaching to provide background material
Additional Information
Graduate Attributes and Skills Not entered
Additional Class Delivery Information Online.
KeywordsData Science,Data Management,Data Strategy
Contacts
Course organiserDr Frederic Bosche
Tel: (0131 6)51 3525
Email: f.bosche@ed.ac.uk
Course secretaryMiss Margaret Robertson
Tel: (0131 6)50 5565
Email: margaret.robertson@ed.ac.uk
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