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University of Technology Sydney

UTS Short Courses Venue (AAI) - Building 10, Level 7

235 Jones Street

Ultimo, NSW 2007

Australia

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Description

Data Analytics (DA) is the discipline of analysing raw data with the purpose of drawing conclusions about that information. Data Analytics is used in many industries to allow companies and organisations to make better business decisions and in the sciences to verify or disprove existing models or theories. This short course, as an entry to advanced data analytics series courses, which are planned by the Advanced Analytics Institute (AAI) this year. The short course will provide a landscape of data analytics, presenting the concepts, fundamental techniques, applications and some projects that have been conducted within AAI.

** Ticketing via the Registration link: https://shortcourses-bookings.uts.edu.au/ClientView/Course/FaceToFaceDetails/2219/AAI17015-Advanced-Data-Analytics-An-Introduction?SiteId=0

This program is particularly useful for
All those involved in BIG DATA for their organisation:

  • Students
  • Researchers
  • Academics
  • Industry Practitioners

Program topics

  • Welcome and AAI Short Course Program briefing
  • Overview of Big Data and Advanced Data Analytics
  • Data Mining in Advanced Analytics
  • Machine Engineering
  • Machine Learning
  • Data Science Innovations: Systems of Insight
  • Marketing Campain Analytics
  • Text Analytics and Sentiment ANalysis
  • Feedback and Closing

Course outcomes
Upon completion of this course students will:

  • Understand why advanced data analytics is essential to your business success
  • Understand the key terms and concepts used in advanced data analytics
  • Understand relations of big data, clouding computing and analytics
  • Be familiar with basic skills of statistics in data analytics, including descriptive analysis, regression, multivariate data analysis
  • Learning basic data mining and data warehousing, visualization and reporting, such as supervised vs unsupervised methods, clustering, association role and frequent mining and so on
  • Knowing key techniques in machine learning, such as Parametric and non-parametric models, learning and inference, Maximum-likelihood estimation, and Bayesian approaches and so on
  • Analyse survey data and ensure analytical results are representative of the market and Analytics Data Architecture
  • Roadmap to Hadoop, Ecosystem & Spark


Presenters

  • Colin Wise – Education Manager, Advanced Analytics Institute at University of Technology Sydney
  • Dr. Qinxue (Max) Meng - Postdoctoral Researcher at UTS: University of Technology Sydney
  • Dr Siamak Tafavogh - is a UTS Adjunct Academic, School of Software, Faculty of Engineering and IT
  • Professor Massimo Piccardi – Professor of Computer Systems with the Faculty of Engineering and Information Technology at University of Technology, Sydney (UTS)
  • Stephan Curikis - Consultant in Advanced Data Analytics
  • Dr. Suresh Sood – Adjunct Academic UTS and Global Consultant in Big Data and Advanced Analytics – Data Scientist with Chartered Accountant – Australia and New Zealand
  • Dr. Shlomo Berkovsky – A senior Researcher at the Data 61 / CSIRO Computational Informatics division.

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Date and Time

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University of Technology Sydney

UTS Short Courses Venue (AAI) - Building 10, Level 7

235 Jones Street

Ultimo, NSW 2007

Australia

View Map

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