Introduction
In recent years, the rise of internet technologies and digital tools in daily life has led to a huge increase in data, known as Big Data. Traditional methods cannot manage this data, so new high-performance and distributed systems like clusters, clouds, MapReduce, and stream computing have been created. The aim of this unit is to give students basic knowledge and understanding of Big Data and distributed computing systems and applications, especially in the context of the Cloud. In other words, the unit will prepare students with the skills needed to build new applications that are scalable, efficient, and able to process Big Data. The key topics are data preparation and exploratory analysis, basics of parallel and distributed systems, Big Data platforms and programming, and basics of cloud computing. The unit will also explain how common cloud infrastructure is changing with these technologies and what future trends may look like.
Summary
| Unit name | Big Data and Cloud Computing |
| Unit code | KXO318 |
| Credit points | 12.5 |
| College/School | Sciences and Engineering School of Information and Communication Technology |
| Discipline | Information & Communication Technology |
| Coordinator | Doctor Matthew Springer |
| Available as an elective? | Yes |
| Delivered By | University of Tasmania |
| Level | Advanced |
Availability
Specific information on 2027 unit availability will be available in August
Learning Outcomes
- Analyse the problems and challenges associated with various datasets, and prepare to apply suitable methods and tools for data processing, analysis, and interpretation.
- Adapt emerging Big Data and cloud technologies to support the building of solutions and applications.
- Design high-performance and cloud applications to support scalable services.
Fee Information
2027 fee information will be available in August.
Requisites
Prerequisites
KXO107Teaching
| Teaching Pattern | On-Campus enrolments in Shanghai:
For this unit, students are expected to attend lectures and tutorial/lab classes, and to keep up to date with MyLO content. |
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| Assessment | Lab Test 1 (20%)|Lab Test 2 (25%)|Tutorial tasks (25%)|Cloud and Big Data Based Processing System (30%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
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The University reserves the right to amend or remove courses and unit availabilities, as appropriate.