Course Title: Cloud Computing
Part A: Course Overview
Course Title: Cloud Computing
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
COSC2640 |
City Campus |
Postgraduate |
140H Computer Science & Information Technology |
Face-to-Face |
Summer2016, Sem 2 2016 |
COSC2640 |
City Campus |
Postgraduate |
171H School of Science |
Face-to-Face |
Sem 2 2017, Sem 2 2018, Sem 2 2019, Sem 1 2020, Sem 1 2021 |
COSC2640 |
City Campus |
Postgraduate |
175H Computing Technologies |
Face-to-Face |
Sem 1 2022, Sem 1 2023, Sem 1 2024 |
Flexible Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
COSC2640 |
City Campus |
Postgraduate |
171H School of Science |
Face-to-Face |
PGRDFlex17 (ZZZZ) |
COSC2640 |
City Campus |
Postgraduate |
171H School of Science |
Face-to-Face |
PGRDFlex18 (ZZZZ) |
COSC2640 |
City Campus |
Postgraduate |
171H School of Science |
Face-to-Face |
PGRDFx2019 (ZZZZ) |
COSC2640 |
City Campus |
Postgraduate |
171H School of Science |
Face-to-Face |
PGRDFlex21 (ZZZZ) |
Course Coordinator: Dr. Qiang Fu
Course Coordinator Phone: .
Course Coordinator Email: qiang.fu@rmit.edu.au
Course Coordinator Location: 14.11.32
Course Coordinator Availability: By appointment via email
Pre-requisite Courses and Assumed Knowledge and Capabilities
Required prior study:
Enforced Prerequisites:
COSC1295 Advanced Programming
OR
COSC2820 Advanced Programming for Data Science
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.
Course Description
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 Amazon Web Service throughout the lectorials, 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.
Objectives/Learning Outcomes/Capability Development
Program Learning Outcomes
This course is an option course so it is not required to contribute to the development of program learning outcomes (PLOs) though it may assist your achievement of several PLOs such as:
PLO1: Knowledge - Apply a broad and coherent set of knowledge and skills for developing user-centric computing solutions for contemporary societal challenges.
PLO2: Problem Solving - Apply systematic problem solving and decision-making methodologies to identify, design and implement computing solutions to real world problems, demonstrating the ability to work independently to self-manage processes and projects.
PLO4: Communication - Communicate effectively with diverse audiences, employing a range of communication methods in interactions to both computing and non-computing personnel.
PLO5: Collaboration and Teamwork - Demonstrate effective teamwork and collaboration by using tools and practices to manage and meet project deliverables.
Course Learning Outcomes
Upon successful completion of this course you should be able to:
- Explain the key concepts and principles of cloud computing and the possible applications of the technology
- Design and develop highly scalable cloud-based applications by creating and configuring virtual machines on the cloud and building private cloud
- Apply big data analysis techniques to store and analyse data in cloud computing
- Investigate and evaluate multiple approaches to cloud system design in order to resolve cloud computing complex problems
- Identify and apply the underlying technologies that enable cloud computing that includes data centre infrastructures, virtualization and containerization, and automation and orchestration in cloud computing solutions
- Design data centres for complex scenarios using emerging networking technologies that include Software-Defined Networking (SDN) and Network Function Virtualization (NFV)
Overview of Learning Activities
The learning activities included in this course are:
- Key concepts and basic principles will be explained in lectorials with current industry examples of applications and solutions.
- Tutorials and labs will help students learn the tools and techniques, such as how to use cloud computing tools offered by industry leaders such as Amazon and practice report writing by analysing case studies.
- Project-based learning, where students will work in a group to analyse and solve industry-related problems with cloud computing solutions
- Private study, working through the course as presented in classes and learning materials, group discussions (including online forums), and gaining practice at solving conceptual and technical problems.
Overview of Learning Resources
You should make extensive use of computer laboratories and relevant software provided by the School. You will be able to access course information and learning materials through Canvas. Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.
The course is supported by the Canvas learning management system which provides specific learning resources. See the RMIT Library Guide at http://rmit.libguides.com/compsci
Overview of Assessment
The assessment for this course comprises a timed practical AWS cloud system development project focusing on your cloud system development abilities using AWS cloud technologies and two written assignments on the underlying technologies that enable cloud computing.
Note: This course has no hurdle requirements.
Assessment Task 1: Timed Practical AWS Cloud System Development
Weighting 40%
This assessment task supports CLOs 1 - 4.
Assessment Task 2: Written assignment 1
Weighting 30%
This assessment task supports CLOs 4-5.
Assessment Task 3: Written assignment 2
Weighting 30%
This assessment task supports CLOs 4-6.