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Curricular information is subject to change
On completion of this module, students should be able to:
- describe and explain the motivations and key concepts of cloud computing;
- compare and contrast the key enabling technologies (i.e., computation, storage, networking, virtualisation, etc.) of cloud computing with their equivalents in the local computer system;
- analyse the strengths and weaknesses of state-of-the-art frameworks based on cloud computing (e.g., Ray, serverless computing);
- efficiently use a public cloud service to improve the performance and maintenance of a big data and/or machine learning project in groups.
Student Effort Type | Hours |
---|---|
Lectures | 24 |
Computer Aided Lab | 6 |
Autonomous Student Learning | 90 |
Total | 120 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Examination: 1-hour on-line testing | Week 10 | No | Graded | No | 50 |
Group Project: Project Report & Demo | Coursework (End of Trimester) | n/a | Graded | No | 50 |
Remediation Type | Remediation Timing |
---|---|
In-Module Resit | Prior to relevant Programme Exam Board |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
Not yet recorded.
Name | Role |
---|---|
Dr Hadi Tabatabaee Malazi | Lecturer / Co-Lecturer |