CS817 - Big Data Tools and Techniques
TIMETABLE | TEACHING MATERIAL |
Credits | 10 |
Level | 5 |
Semester | Semester 2 |
Availability | MSc Data Science |
Prerequisites | N/A |
Learning Activities Breakdown | Lectures: 10 | Labs: 10 Self study: 80 |
Assessment | 100% written exam |
Lecturer | Nur Muhamad Naim |
Aims and Objectives
The module aims to endow students with:
· An understanding of the new challenges posed by the advent for big data, as they refer to its modelling, storage, and access.
· Exposure to a number of different big data technologies and techniques, showing how they can achieve efficiency and scalability, while also addressing design trade-offs and their impacts.
Learning Outcomes
- Familiarity with a number of different cloud NoSQL systems and their design and implementation, showing how they can achieve efficiency and scalability, while also addressing design trade-offs and their impacts
- Familiarity with the Map-Reduce programming paradigm, to enable students write program which can execute in massively parallel cloud based infrastructures
Syllabus
tbc
Recommended Reading
This list is indicative only – the class lecturer may recommend alternative reading material. Please do not purchase any of the reading material listed below until you have confirmed with the class lecturer that it will be used for this class.
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Last updated: 2022-10-05 00:09:52