Advanced Data Analytics

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Contact information

For further information or to request a quotation, please contact the Professional Education Courses Unit on:

Enquiries Phone: 02 5114 5573

Enquiries Email: ProfEdCourses@adfa.edu.au

In-house delivery

UNSW Canberra Professional Education Courses may be available for in-house delivery at your organisation's premises. In-house courses allow maximum attendance without the additional travel costs. Courses can be developed to suit the specific staff development and training needs of your organisation. Recommended for groups of 10 or more.

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.

In today’s complex and dynamic world, decision makers are faced with more and more complicated problem environments. To address these complicated problems, decision makers express the situation by creating models representing a simplification of the real world, which act as a workbench for testing and confirming ideas and solutions to the problem faced. The benefit of building and using models is to provide an improved understanding of the situation or problem being faced. One of the most important and widely used tools for developing models is the spreadsheet. Data Analytics (DA) is the process of collecting and examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of spreadsheet software. These data collection and manipulation tools are some of the more important ingredients in Data Analytics technologies and techniques, which are widely used in public and private organisations to enable those organizations to make better informed business decisions.  

The spreadsheet tools, that would be covered in this short course, are complex charts, sparklines, scroll bars, dynamic and interactive targets lines, radio buttons, and dashboards. The course includes hands-on training using spreadsheet tools for developing dashboards. 

This course is divided into two modules as follows. 

  • Module 1: Basic Data Analytics (3 days) 

  • Module 2: Advanced Topics in Data Analytics (2 days) 

  • Module 1 + Module 2: Advanced Data Analytics 

The participants can do either Module 1 or both Modules. However, Module 1 is a prerequisite for Module 2. 

Presenters

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.

Course Information

Module 1: This three-day course addressing Data Analytics using spreadsheets. The course addresses the concept of data elements, different classifications of data and levels of measurement. Data sources are briefly mentioned and the different modes of sampling are highlighted. Basic EXCEL worksheet operations are covered such as SUM, SUMIF, SUMPRODUCT, COUNT, COUNTIF, VLOOKUP and HLOOKUP and illustrated through hands-on exercises.  Data visualisation using EXCEL charting techniques will be addressed. Data Tables, Pivot Tables, Regression and Trend Analysis will be covered. 

Module 2: This two-day module builds upon the course “Basic Data Analytics”. The spreadsheet tools, that would be covered in this short course, are complex charts, sparklines, scroll bars, dynamic and interactive targets lines, radio buttons, and dashboards. 

  • The participants will learn a good number of spreadsheet tools, and gain skills on the use of Excel in manipulating data. 

  • 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 12 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.