ENGG2851: Data Analytics for Project Management (2014 - Semester 1)

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Unit: ENGG2851: Data Analytics for Project Management (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Intermediate
Faculty/School: Project Management
Unit Coordinator/s: Dr Piraveenan, Mahendrarajah
Session options: Semester 1
Versions for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: ENGG1850 AND MATH1001 AND MATH1002 AND MATH1003 AND MATH1005.
Brief Handbook Description: Project Management Data analytics (DA) provides extensive coverage related to examining raw data with the purpose of drawing conclusions about that information. It is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify or disprove existing models or theories. Here, we focus our effort on providing in-depth knowledge and skills to students focusing on inference, process of deriving a conclusion based solely on what is already known by the project manager.
Assumed Knowledge: None.
Lecturer/s: Dr Piraveenan, Mahendrarajah
Timetable: ENGG2851 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Lecture 2.00 1 13
2 Tutorial 1.00 1 12
3 Laboratory 1.00 1 12
4 Independent Study 6.00 1 12
T&L Activities: Tutorials:

Labs:

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

Project Methods (Level 3)
1. Ability to select and apply appropriate methods in modelling and analysing complex project management scenarios, taking into account the requirements and limitations of the method chosen.
2. Ability to use decision theory, in particular games, project scheduling and Markov models, in modelling complex management decisions.
3. Ability to conceptualise business systems as networks.
4. Ability to use object-oriented programming in capturing and modelling real world systems.
5. Ability to use linear programming in in capturing and modelling real world systems.
6. Ability to use dynamic programming in capturing and modelling real world systems.
7. Ability to apply optimisation algorithms to complex management decisions.
8. Understanding of methods for effective data storage and retrieval.
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Theory Assignment No 20.00 Week 6 1, 2,
2 Programming Assignment A No 15.00 Week 9 3, 4, 5, 8,
3 Programming Assignment B No 15.00 Week 13 4, 6, 7, 8,
4 Final Exam No 50.00 Exam Period 1, 2, 3, 4, 5, 6, 7,
Grading:
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Policies & Procedures: See the policies page of the faculty website at http://sydney.edu.au/engineering/student-policies/ for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Recommended Reference/s: Note: References are provided for guidance purposes only. Students are advised to consult these books in the university library. Purchase is not required.

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 Decision-making in Project Management.
Week 2 Data representation in Project Management.
Introduction to programming.
Week 3 Decision theory and games.
Week 4 Markov models.
Week 5 Project scheduling.
Week 6 Network models. Topological analysis.
Assessment Due: Theory Assignment
Week 7 Network models. Topological analysis.
Week 8 Linear programming.
Week 9 Simplex method.
Assessment Due: Programming Assignment A
Week 10 Dynamic programming.
Week 11 Simulation modelling.
Week 12 Optimisation theory.
Week 13 Assessment Due: Programming Assignment B
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Aeronautical Engineering / Project Management 2012, 2013, 2014
Aeronautical Engineering (Space) / Project Management 2012, 2013, 2014
Biomedical Engineering / Project Management 2013, 2014
Chemical & Biomolecular Engineering / Project Management 2012, 2013, 2014
Civil Engineering / Project Management 2012, 2013, 2014
Electrical Engineering / Project Management 2012, 2013, 2014
Electrical Engineering (Power) / Project Management 2012, 2013, 2014
Aeronautical / Project Management 2015
Aeronautical (Space) / Project Management 2015
Biomedical / Project Management 2015
Chemical & Biomolecular / Project Management 2015
Civil / Project Management 2015
Mechanical / Project Management 2015
Mechanical (Space) / Project Management 2015
Mechatronic / Project Management 2015
Mechatronic (Space) / Project Management 2015
Mechanical Engineering (Biomedical) / Project Management 2012
Mechanical Engineering / Project Management 2012, 2013, 2014
Mechanical Engineering (Space) / Project Management 2012, 2013, 2014
Mechatronic Engineering / Project Management 2012, 2013, 2014
Mechatronic Engineering (Space) / Project Management 2012, 2013, 2014
Software Engineering / Project Management 2012, 2013, 2014
Bachelor of Project Management (Built Environment) 2012, 2013, 2014, 2015
Bachelor of Project Management (Civil Engineering Science) 2012, 2013, 2014, 2015
Bachelor of Project Management (Software) 2012, 2013, 2014, 2015

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
Project Leadership (Level 2) No 0%
Project Methods (Level 3) No 100%
Project Development (Level 2) No 0%

These goals are selected from Project Management Learning Progression Table which defines overall goals for courses where this unit is primarily offered. See Project Management Learning Progression Table for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.