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Unit outline_

ENGG2851: Project Analytics

Semester 1, 2022 [Normal day] - Camperdown/Darlington, Sydney

Project data analysis is required to inform decision making. This becomes increasingly significant as project becomes larger and more complex. This subject introduces students to a variety of fundamental analytical techniques used in project management including consideration of their assumptions, limitations, how and when they should be applied.

Unit details and rules

Academic unit Project Management
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Mehdi Rajabi Asadabadi, mehdi.rajabiasadabadi@sydney.edu.au
Lecturer(s) Mehdi Rajabi Asadabadi, mehdi.rajabiasadabadi@sydney.edu.au
Tutor(s) Upul Senanayake, upul.senanayake@sydney.edu.au
Rizwan Ahmad, rizwan.ahmad@sydney.edu.au
Type Description Weight Due Length
Participation Participation
Activities to complete during or after the class.
20% Ongoing Ongoing
Outcomes assessed: LO1 LO5 LO4 LO3 LO2
Assignment Individual Assignment
Students will clean and analyse the given data set
20% Week 07
Due date: 10 Apr 2022 at 20:00
1500 words
Outcomes assessed: LO1 LO3 LO4 LO5
Online task Online Quiz
Students will do an online quiz based on the content covered in week1-week5
15% Week 08
Due date: 15 Apr 2022 at 20:00
45 minutes
Outcomes assessed: LO1 LO4 LO3 LO2
Assignment group assignment Group Assignment
Students will work in groups on a given case study
20% Week 11
Due date: 15 May 2022 at 18:00
2000 words
Outcomes assessed: LO2 LO3 LO4 LO5
Assignment group assignment Group Presentation
Students group will be presenting their group assignments to class
10% Week 12
Due date: 20 May 2022 at 18:00
5 Minutes
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
Online task Online Quiz
Students will do an online quiz
15% Week 13
Due date: 27 May 2022 at 20:00
45 minutes
Outcomes assessed: LO1 LO7 LO6 LO5 LO4 LO3 LO2
group assignment = group assignment ?

Assessment summary

Weekly assessments: Studensts will be asked to submit solutions to questions asked during the workshops

Class Participation: Students will be marked on their engaement in class both with peers and with teacher

Individual Assignment: Students will be doing some problem solving related to a given project. 

Group Assignment : Students will be working in groups of 4-5 to use analytical skills to help management gain insights on the given case study.

 

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

 
 
 
 
 
 

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:

Late submissions will incur a penalty of 5% per day for up to 7 days starting directly after the cut-off time. This means 5% will be deducted even if submitted on the due day but after the cut-off time. After one week, assessments will no longer be marked and receive a 0 mark.

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
Multiple weeks pre-class and post-class independent learning Independent study (130 hr) LO1 LO2 LO3 LO4 LO5
Week 01 Overview and introduction Workshop (2 hr) LO1
Week 02 Data Basics Workshop (2 hr) LO1 LO3 LO4
Week 03 Basic analytical tools Workshop (2 hr) LO2 LO3 LO4 LO5
Week 04 Descriptive Analytics Workshop (2 hr) LO2 LO4 LO5 LO6 LO7
Week 05 Diagnostic Analytics Workshop (2 hr) LO2 LO3 LO4 LO5 LO6 LO7
Week 06 Data Visualisation and Dash Boarding Workshop (2 hr) LO3 LO4 LO5
Week 07 Predictive Analytics Workshop (2 hr) LO1 LO2 LO3 LO4 LO6 LO7
Week 08 Online Quiz Workshop (2 hr) LO1 LO2 LO3 LO4
Week 09 Prescriptive Analytics Workshop (2 hr) LO2 LO3 LO4 LO5
Week 10 Automated Analytical Tools Workshop (2 hr) LO3 LO4 LO5
Week 11 Student Presentations Workshop (2 hr) LO3 LO4 LO5
Week 12 Student Presentations Workshop (2 hr) LO3 LO4 LO5
Week 13 Online Quiz Workshop (2 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7

Attendance and class requirements

Study commitment: 

This unit of study is comprised of online learning and workshops. The workshop participation forms a significant component of the course and will demonstrate specific techniques discussed at a theoretical level in online learning. Workshop participants will include case study reviews, discussions, and some problem-solving exercises carried out individually or in groups. These sessions will also introduce students to the team-based nature of projects and provide opportunities for small group problem solving and discussion, based around case studies and model problems arising from realistic technical and business scenarios.

Attendance requirement

It is a requirement of this course that you must attend more than 75% of the workshops. This means students who fail to attend more than 3 workshops without prior approval will fail the course.

 
 
 
 
 
 

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.

Required readings

There are no prescribed readings for the course. Relevant readings will be embedded in weekly modules.

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. Explain the purpose of measurement in different project contexts (hard/soft, large/small, complex/not, different domains, etc.)
  • LO2. Explain the uses and limitations of measurement in different project contexts
  • LO3. Explore a range of analytical tools and techniques for monitoring and control that are appropriate to different project contexts
  • LO4. Select and apply analytic tools and techniques to analyse situations, financial and organisational data, and trends
  • LO5. Apply analytical tools and techniques to specific project contexts
  • LO6. Monitor progress and make any necessary adjustments to parameters
  • LO7. Review and evaluate project performance at handover

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.

Changes made in learning activities and assessments to suit 13 week semester

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.