Big Data and Cloud Computing
UndergraduateTAS-KIT3182026
Course information for 2026 intake
- Study method
- 100% online
- Assessments
- 100% online
- Enrol by
- 15 Feb 2026
- Entry requirements
- Part of a degree
- Duration
- 12 weeks
- Start dates
- 23 Feb 2026
- Price from
- $2,919
- Upfront cost
- $0
- Loan available
- HECS-HELP and FEE-HELP available
Big Data and Cloud Computing
About this subject
On successful completion of this subject, students will be able to:
- 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.
- Introduction and basics
- Giving mix of topics to organise.
- Big Data-Map Reduce
- Big Data-SPARK I
- Big Data-Spark II
- No-SQL Databases- Mongo DB
- Thread and Network Programming
- Parallel and Distributed Computing
- Cloud Computing Introduction
- Amazon EC2-1
- Amazon EC2-2
- Amazon EC2-3
- Amazon EC2-4
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 subject 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 subject 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 subject will also explain how common cloud infrastructure is changing with these technologies and what future trends may look like.
- Lab Test 1 (20%)
- Lab Test 2 (25%)
- Tutorial Tasks (25%)
- Cloud and Big Data Based Processing System (30%)
For textbook details check your university's handbook, website or learning management system (LMS).
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- QS World University Ranking 2026, within Australia:
- 20
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- 14
Entry requirements
Part of a degree
To enrol in this subject you must be accepted into one of the following degrees:
Core
- TAS-IAI-DEG-2026 - Bachelor of Information and Communication Technology (Artificial Intelligence)
Prior study
You must either have successfully completed the following subject(s) before starting this subject, or currently be enrolled in the following subject(s) in a prior study period; or enrol in the following subject(s) to study prior to this subject:
Please note that your enrolment in this subject is conditional on successful completion of these prerequisite subject(s). If you study the prerequisite subject(s) in the study period immediately prior to studying this subject, your result for the prerequisite subject(s) will not be finalised prior to the close of enrolment. In this situation, should you not complete your prerequisite subject(s) successfully you should not continue with your enrolment in this subject. If you are currently enrolled in the prerequisite subject(s) and believe you may not complete these all successfully, it is your responsibility to reschedule your study of this subject to give you time to re-attempt the prerequisite subject(s).
Additional requirements
- Other requirements - Teaching Arrangements: Lectures 2-hrs weekly, Tutorials 2-hrs weekly, Independent learning 2 hrs weekly (average)
Study load
- 0.125 EFTSL
- This is in the range of 10 to 12 hours of study each week.
Equivalent full time study load (EFTSL) is one way to calculate your study load. One (1.0) EFTSL is equivalent to a full-time study load for one year.
Find out more information on Commonwealth Loans to understand what this means to your eligibility for financial support.
Related degrees
Once you’ve completed this subject it can be credited towards one of the following courses
Bachelor of Information and Communication Technology (Artificial Intelligence)
UndergraduateTAS-IAI-DEG