Cloud Computing
UndergraduateRMI-CPT3502024
Course information for 2024 intake
Round off your IT course with an exploration of cloud platforms, apps, and databases. Elevate your coding to include advanced cloud programming. Unpack big data and cloud storage. Complete problem-solving tasks and gain hands-on experience.
Enrolments for this course are closed, but you may have other options to start studying now. Book a consultation to learn more.
- Study method
- 100% online
- Assessments
- Subject may require attendance
- Entry requirements
- Part of a degree
- Duration
- 13 weeks
- Loan available
- HECS-HELP and FEE-HELP available
Cloud Computing
About this subject
Note that this is an advanced IT course and the material presented within it will be targeted at students who are in the final stage of their studies towards the Bachelor of Information Technology.
Upon successful completion of this course you should be able to:
- Develop and deploy cloud application using popular cloud platforms,
- Design and develop highly scalable cloud-based applications by creating and configuring virtual machines on the cloud and building private cloud.
- Explain and identify the techniques of big data analysis in cloud.
- Compare, contrast, and evaluate the key trade-offs between multiple approaches to cloud system design, and Identify appropriate design choices when solving real-world cloud computing problems.
- Write comprehensive case studies analysing and contrasting different cloud computing solutions.
- Make recommendations on cloud computing solutions for an enterprise.
- Introduction / Setup
- Building Cloud Applications
- Amazon Web Services (AWS)
- Cloud Applications
- Parallel and Distributed Computing
- Cloud Databases
- Serverless Computing
- Data Visualisation
- Data Mining
- Real-time Data Analysis
- Internet of Things (IOT) / Cloud Privacy
- Revision
Cloud Computing is a large-scale distributed computing paradigm which has become a driving force for information technology over the past several years. The exponential growth data size in scientific instrumentation/simulation and social media has triggered the wider use of cloud computing services.
This course covers topics and technologies related to Cloud Computing and their practical implementations. You should explore different architectural models of cloud computing, the concepts of virtualisation and cloud orchestration. You should gain hands-on experience with various features of popular cloud platforms such as Google App Engine and Amazon Web Service throughout the lectures, tutorials, and laboratory sessions. Advanced cloud programming paradigms such as Hadoop’s MapReduce is also included in the course. You should also learn the concept of modern Big Data analysis on cloud platforms using various data mining tools and techniques. The lab sessions cover cloud application development and deployment, use of cloud storage, creation and configuration of virtual machines and data analysis on cloud using data mining tools. Different application scenarios from popular domains that leverage the cloud technologies such as remote healthcare and social networks will be explained. The theoretical knowledge, practical sessions and assignments aim to help you to build your skills to develop large-scale industry standard applications using cloud platforms and tools.
This course focuses on learning emerging issues related to Cloud computing technology. The objectives are:
- Understand various basic concepts related to cloud computing technologies
- Understand the architecture and concept of different cloud models: IaaS, PaaS, SaaS
- Understand big data analysis tools and techniques
- Understand the underlying principle of cloud virtualization, cloud storage, data management and data visualization.
- Understand different cloud programming platforms and tools
- Have details knowledge on reading and writing in cloud storage
- Be familiar with application development and deployment using cloud platforms
- Create application by utilizing cloud platforms such as Google app Engine and Amazon Web Services (AWS)
- Learn to develop scalable applications using AWS features.
- Learn basic concepts of MapReduce programming models for big data analysis on cloud.
Practical problem-solving tasks:
A series of small tasks which will help build up your capability working with Cloud Computing technologies and applying Cloud Computing design considerations and techniques to implement cloud-based solutions to client system requirements.
Practical problem-solving project:
A larger project in which you will be designing and developing a highly scalable application in which you will choose a programming language, cloud platform and services / API which best fit the requirements of the proposed system.
Final Exam:
An invigilated final exam which will assess your understanding of and ability to apply key concepts, design considerations, and platforms / technologies in the cloud computing discipline.- Practical Problem-Solving Tasks (15%)
- Practical Problem-Solving Project (35%)
- Final Examination (50%)
For textbook details check your university's handbook, website or learning management system (LMS).
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Entry requirements
To enrol in this subject, you must be admitted into a degree.
Prior study
You must have successfully completed the following subject(s) before starting this subject:
Others
Enforced Prerequisite:
CPT225 Advanced Programming Techniques
OR
CPT222 Software Arch: Design and Implementation
Required prior study: None
Assumed knowledge: It is assumed that you have:
- basic Python, JavaScript and PHP programming skills
- basic understanding of Data Communications and Networking Technologies
- basic understanding of College level (or first year undergrad type) Mathematics
- ability to write technical reports
Note it is a condition of enrolment at RMIT that you accept responsibility for ensuring that you have completed the prerequisite/s and agree to concurrently enrol in co-requisite courses before enrolling in a course.
Additional requirements
- Software requirements - Subscription to Google and/or Amazon Web Services (AWS) may be required - details TBC.
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.