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Unit outline_

OCMP5349: Cloud Computing

Semester 2b, 2023 [Online] - Online Program

This unit covers topics of active and cutting-edge research within IT in the area of 'Cloud Computing'. Cloud Computing is an emerging paradigm of utilising large-scale computing services over the Internet that will affect individual and organization's computing needs from small to large. Over the last decade, many cloud computing platforms have been set up by companies like Google, Yahoo!, Amazon, Microsoft, Salesforce, Ebay and Facebook. Some of the platforms are open to public via various pricing models. They operate at different levels and enable business to harness different computing power from the cloud. In this course, we will describe the important enabling technologies of cloud computing, explore the state-of-the art platforms and the existing services, and examine the challenges and opportunities of adopting cloud computing. The unit will be organized as a series of presentations and discussions of seminal and timely research papers and articles. Students are expected to read all papers, to lead discussions on some of the papers and to complete a hands-on cloud-programming project.

Unit details and rules

Academic unit Computer Science
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
COMP5349 or COMP4349
Assumed knowledge
? 

Basic knowledge of computer networks as covered in INFO1112 or COMP9201 or COMP9601 (or equivalent UoS from different institutions)

Available to study abroad and exchange students

No

Teaching staff

Coordinator Ali Anaissi, ali.anaissi@sydney.edu.au
Type Description Weight Due Length
Assignment Project
A term long project
20% Week 06 6 weeks
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
Supervised exam
? 
hurdle task
Final Exam
Final Exam taken in Week 8
50% Week 08 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
Small continuous assessment AWS Challenge Labs
Challenge Labs taken in the AWS Instance of Canvas.
30% Weekly 60 to 90 minutes per week
Outcomes assessed: LO1 LO7 LO6 LO5 LO4 LO3 LO2
hurdle task = hurdle task ?

Assessment summary

  • Challenge Labs: Each week, you will complete a Challenge Lab using AWS Academy's Canvas platform where you will demonstrate practical skills in a particular area of Cloud Architecting.
  • Project: You will design and implement a Cloud solution to solve a set problem using AWS Academy's Canvas platform.
  • Final Exam: You will answer a series of questions that test your understanding of Cloud Computing concepts that you have studied in this unit under examination conditions.

The final exam is a hurdle task. You must score at least 40% in the final exam in order to pass this unit.

Detailed information for each assessment can be found on Canvas. Assessment rubrics and submission instructions are published on Canvas.

Assessment criteria

Result name Mark range Description
High Distinction 85 - 100 Excellent course work
Distinction 75 - 84 Very good course work
Credit 65 - 74 Good course work
Pass 50 - 64 Fair course work
Fail 0 - 49 When you don’t meet the learning outcomes of the unit to a satisfactory standard.

 

It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Challenge Labs that are submitted late will be awarded zero marks. Standard late penalties apply for the Project.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Cloud Computing Overview Lecture (4.18 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Cloud Computing Overview Workshop (1.5 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Week 02 Cloud Computing Services Lecture (3.5 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Cloud Computing Services Workshop (1.5 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Week 03 Cloud Database Services Lecture (4.75 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Cloud Database Services Workshop (1.5 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Week 04 Cloud Networking and Security Lecture (4.45 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Cloud Networking and Security Workshop (1.5 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Week 05 Cloud Scalability and Automation Lecture (4.02 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Cloud Scalability and Automation Workshop (1.5 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Week 06 Micro Services Architecture Lecture (2.97 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7
Micro Services Architecture Workshop (1.5 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. develop a comprehensive understanding of cloud computing concepts, architecture, and design principles.
  • LO2. explain cloud-enabling technologies, including virtualization and containerization
  • LO3. gain proficiency in using cloud-based tools and technologies, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP)
  • LO4. acquire expertise in different cloud storage and databases
  • LO5. gain expertise in securing cloud-based solutions, including data protection and network security.
  • LO6. acquire an understanding of emerging cloud technologies and trends, such as microservices architecture and serverless computing.
  • LO7. create a solution architecture for transitioning to the cloud

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

New unit outline

Disclaimer

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