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This course will be run as a live simulcast online course presented through Microsoft Teams. You will be required to use Excel 2016 or later during this course.
Decision analytics refers to a systematic, quantitative, iterative and interactive approach to addressing and evaluating important decision choices confronted by organisations in the private and public sector. This short course on Advanced to Decision Analytics is designed to provide basic understanding of the principles and practices of decision analytics, to introduce several decision-making tools for analysing complex decision problem environments, and for making appropriate decisions within that environment, and to strengthen the individual’s decision making skills.
The decision-making tools, that would be covered in this short course, are suitable for tactical and operational level decision problems. Typical examples of such problems include project selection, budget allocation, resource allocation and planning, transportation planning, rostering and scheduling, forecasting, waiting line problems, and multiple objectives decision making. The course includes hands-on training with spreadsheet based tools for decision making.
This course is divided into two modules as follows.
Module 1: Basic Decision Analytics (3 days)
Module 2: Advanced Topics Decision Analytics (2 days)
Module 1 + Module 2: Advanced Decision Analytics
The participants can do either Module 1 or both Modules. However, Module 1 is a prerequisite for Module 2.
Prof. Charles S Newton obtained his PhD in Nuclear Physics from the ANU in 1975. He is an Emeritus Professor in the School of Engineering and IT, UNSW Canberra. He was the Head of the former School of Computer Science (currently a part of School of Engineering and IT) from 1993 to 2003. He was the President of National Committee of the Australian Society for Operations Research (ASOR) in 1995-96. He is the co-author of the book Optimization Modelling: A Practical Approach, Taylor & Francis /CRC Press, Boca Raton. Prof. Newton is well-known, both nationally and internationally, for his practice in Operations Research specifically for defence related problems.
Prof. Ruhul A Sarker obtained his Ph.D. in Operations Research from Dalhousie University (former TUNS), Halifax, Canada in 1992. He is currently a Professor in the School of Engineering and IT, co-ordinator of the Master of Decision Analytics program in the school, and the Director of Faculty Postgraduate Research at UNSW Canberra (located at ADFA), Australia. He was the Deputy Head of School (Research) from 2011 to 2014. Prof. Sarker’s broad teaching and research interests include decision analytics, computational intelligence, operations research, and applied optimization. He is the lead author of the book Optimization Modelling: A Practical Approach, Taylor & Francis /CRC Press, Boca Raton. Prof. Sarker has successfully obtained more than $1.5million external research grants. He was a member of the national executive committee of the Australian Society for Operations Research (ASOR) and Editor-in-chief of ASOR Bulletin from 2000 to 2011. As recognition of Prof. Sarker’s contributions to ASOR and Operations Research, ASOR awarded him an ASOR Medal (2011) and Special Service Certificate (2009). Currently, he is an associate editor of three international journals.
Module 1: This three-day module addresses well-structured Decision Analytics problems using spreadsheets. The course addresses the concepts of analytics and introduces few basic decision analytics tools such as linear program and integer program for practical decision making. Examples of a wide variety of problems that can be solved using an Add-in to EXCEL (Solver), will be covered. Problems involving product mix, capital budgeting, transportation, assignment and networks to name a few will be presented.
Module 2: This two-day module builds upon the course “Basic Decision Analytics”. The course addresses the concepts of decision making with goal achievement and multiple objectives. Other topics include managing tasks and resources in network problems and managing waiting line and service utilisation. Non-linear interactions in decision problems and evolutionary optimisation will be discussed. A number of practical problems will be solved using EXCEL Solver.
The participants will learn a good number of decision making tools and techniques, and gain skills on the use of Excel Solver in solving practical decision making problems.
Statement of Attendance is provided upon completion. However, to obtain competency certificate, the participants must demonstrate their knowledge gained in the course by completing a few small scale problem solving exercises during the course.
UNSW Canberra allows students who have successfully completed a minimum of 10 days of approved professional education advanced short courses to use those courses as credit in eligible postgraduate programs.
Courses will be held subject to sufficient registrations. UNSW Canberra reserves the right to cancel a course up to five working days prior to commencement of the course. If a course is cancelled, you will have the opportunity to transfer your registration or be issued a full refund. If registrant cancels within 10 days of course commencement, a 50% registration fee will apply. UNSW Canberra is a registered ACT provider under ESOS Act 2000-CRICOS provider Code 00098G.