Training course

Housing Market Analytics: Turning Data to Insights

Develop an in-depth understanding of housing market economics, analytics and modelling to gain a competitive edge as a real estate professional, investor, developer, policy maker, fund manager, or home buyer in the Australian Context

Analytical frameworks

Comprehensive coverage of analytical techniques and frameworks used in the property industry

Real world data sets

Learn through hand on working with real world data sets, no coding skills are required

Contemporary content

Develop contemporary knowledge and skills in real estate economics and analytics


A hard copy book (100 pages) and data files will be delivered to your nominated address

Duration: 4 weeks

Scheduled to complete in 4 weeks, or totally flexible depending on your pace

Fee (Book only): AU$199

Gain a competitive edge in property analytics that sets a strong foundation for success


Residential real estate underpins Australia’s wealth: $9.6 trillion or 56% of household wealth is held in housing, $500 billion worth of real estate is transferred per year. The housing industry creates 1.4 million jobs and generates billions of dollars in tax revenue to the state and federal governments.

There is a growing demand for real estate professionals to be equipped with contemporary tools and analytical frameworks to enable turning data to actionable insights, amid property data is becoming increasingly available to the public. is proud to offer the first data analytics and modelling course dedicated to analysing the Australian housing market: Housing Market Analytics: Turning Data to Insights.

You’ll explore the theory and the analytical frameworks to gain in-depth knowledge about the dynamics of the Australian housing market, learn how to use data and modelling techniques to value property, use data analytics to forecast the future trends of the key market indicators, and carry out rigorous due diligence for any property or a sub-market.

This course is designed by Dr. Kevin Hoang, who has earned a PhD in economics from the University of New South Wales (UNSW) and has possessed years of experience in the domain of the Australian housing market analytics.

Click Buy Now will lead you to PayPal payment platform, once paid the Book and excel data files will be emailed to your nominated email address.

  • Possessing a good knowledge of mathematics or statistics at high school level 
  • Proficiency in working with Excel
  • No coding skill is required
  • No prior experience or training in real estate is required
  • A positive mind to learn data-driven techniques for informed decision making
Target audiences
  • Property professionals
  • Property investors
  • Home buyers
  • Property developers
  • Fund managers
  • Policy makers
  • Financial analysts
  • Agents
  • Anyone who wants to learn competitive edge in real estate data analytics
  • Comprehensive coverage of analytical techniques and frameworks used in the property industry: valuation, forecasting and risk management
  • Learn through hand on working with real world data sets, no coding skills are required
  • Overview of the long-term trends, and the key drivers that will drive the market in the future
  • Developing analytical skills in working with property data, and turn it to insights for confident decisioning 
  • Make more informed property investment decisions to maximise returns and minimise risks
Course management
  • Start date: any time
  • Self pace learning: hard copy book and data files will be sent to your nominated address

Program Modules

MODULE 1: The Australian housing market: an overview, prices, growth, rent, volatility and performance

Understand the economic theories that underpin the formation and evolution of cities; review the role of the housing market in the economy; examine historical data such as trends and patterns of the key indicators including prices, growth, rent, volatility and returns.

MODULE 2: Supply and demand: the market fundamentals

Understand the forces that drive supply and demand in housing market and how these forces determine prices and trends; frame a solid explanation about the differences in prices and growth paths between cities.

MODULE 3: Growth cycles analytics

Examine the characteristics of property cycles and identify the phase of the housing market at any point of time for informed decisioning.

MODULE 4: Forecasting: theory and practice

Learn how to use historical data and forecasting methods to predict the future housing market trends.

MODULE 5: Property valuation methods: theory and practice of automated home valuation modelling and cash flow modelling

Understand the theory of the hedonic modelling approach that underpins the modern automated home valuation models currently offered by the leading companies such as Corelogic/RP Data; use real property data to build your own automated home valuation model for a suburb; and carry out a valuation for a specific property or a building.

MODULE 6: Simulation modelling for risk management in property investment

Learn to use analytical approaches to manage uncertainties in property investment; carry our the Monte Carlo simulation method using real world data set and interpret the results for decision making.


Dr. Kevin Hoang is a senior economist with 20 years of experience working in Australia and Asia. He has held positions in public, industry and academic settings: a research fellow in economics at the University of New South Wales, Sydney, and a senior economist in the domain of Australian property market analytics, in charge of monitoring the Australian property market to identify the emerging investment opportunities, backed by economics, data and advanced analytics. Dr. Hoang currently is the Director of the Housing Market Modelling Program of, dedicated to develop cutting-edge analytical models and provide training course in housing market analytics to empower evidence-based decision making for home buyers, investors, developers and property service providers. Dr. Hoang earned a Ph.D in economics from the University of New South Wales in 2012 and was a Japan-IMF scholar in 2004-2006.