Australia's largest dual-sector institute, offering both TAFE and higher education, RMIT University proudly delivers work-related education and practical research relevant to current business and community needs. More than 60,000 students study with RMIT, and many of their degrees are available through Open Universities Australia.
QS RANKING 2021
Times Higher Education Ranking 2021
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
You must have successfully completed the following subject(s) before starting this subject:
- Software requirements - Subscription to Google and/or Amazon Web Services (AWS) may be required - details TBC.
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%)