Courses & Units

Big Data and Cloud Computing KIT318


In recent years, due to advancement of internet technologies and instrumentation of every part of our life, we have noticed a huge surge in data available to us. This revolution is termed as Big Data. This Big Data cannot be processed or managed by any traditional methods of processing. This has led to development of several high performance and distributed computing platforms and programming frameworks. The design of such platforms relies on distributed computing concepts which are implemented in the form of systems such as Clusters and Clouds, and Big Data frameworks such as MapReduce and Stream Computing. These systems play an important role in todays' research, academia or industries by providing the processing of data generated from a variety of networked resources, e.g. large data stores and information repositories, expensive instruments, social media, sensors networks, and multimedia services for a wide range of applications. The aim of this unit is to provide students with the foundation knowledge and understanding of Big Data and distributed computing systems and applications especially in context of Cloud. In other words, this unit will equip students with essential knowledge that is needed for building next-generation applications that are scalable and efficient and can process Big Data. Key topics that will be covered: parallel and distributed systems basics, Big Data platforms and programming and Cloud computing. The unit will also explain how the business models of enterprises are changing with these forms of computing that provide large storage and computation space without purchasing expensive computer systems.


Unit name Big Data and Cloud Computing
Unit code KIT318
Credit points 12.5
College/School College of Sciences and Engineering
School of Information and Communication Technology
Discipline Information & Communication Technology
Coordinator Doctor Saurabh Garg
Available as an elective? Yes
Delivered By University of Tasmania
Level Advanced


Location Study period Attendance options Available to
Hobart Semester 1 On-Campus International Domestic
Launceston Semester 1 On-Campus International Domestic


International students
Domestic students

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Key Dates

Study Period Start date Census date WW date End date
Semester 1 26/2/2024 22/3/2024 15/4/2024 2/6/2024

* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).

Unit census dates currently displaying for 2024 are indicative and subject to change. Finalised census dates for 2024 will be available from the 1st October 2023. Note census date cutoff is 11.59pm AEST (AEDT during October to March).

About Census Dates

Learning Outcomes

  • Analyse the problems and challenges associated with building distributed computing applications;
  • Adapt the emerging big data and cloud technologies to support business applications.
  • Design high performance and cloud applications to support scalable online services.
  • Design big data processing applications to efficiently process high volume and velocity data

Fee Information

The 2024 Commonwealth Supported Place (CSP) rates are still being finalised by the Government and we will update the domestic fee information as soon as we have more details.





Teaching Pattern

Lectures: 2 hr/wk 
Tutorials: 3 hr/wk - For this unit, students are expected to attend on-campus tutorials; an online tutorial will be available for students with special circumstances (permission is required to attend the online tutorial)

AssessmentBig Data Assignment (15%)|Cloud and Big Data Based Processing System (20%)|Tutorial work (30%)|Test (35%)
TimetableView the lecture timetable | View the full unit timetable



Required readings will be listed in the unit outline prior to the start of classes.

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