Introduction to Data Science
and Machine Learning for Real Estate
Get an in-depth understanding of emerging business opportunities, trends, and disruptions in this non-technical seminar that demystifies the technologies at the intersection of data science and real estate.

ONLINE SEMINAR

[S1] Seminar: Introduction to Data Science and Machine Learning for Real Estate

In this live, online seminar, PhD instructors and industry practitioner guest speakers will demystify the world of data science, machine learning, and artificial intelligence, and discuss their specific applications to the real estate industry. Attention will be paid to how these techniques are already being used in the field today, and the trends that will impact the industry in the near future.

Technical topics explained include:

  • Data Science methods for Real Estate
  • Data sources & Price Indexation
  • Automated Valuation & Forecasting
  • Clustering, Spatial Intelligence, & Geographic Information Systems
  • Emerging technologies

This seminar is for you, if:

  • You want to explore making data-driven real estate decisions (including using your company’s data), but don’t know where to start;
  • You need to work with or hire technical and data science employees or consultants, but don’t know what to ask for or what’s possible; or
  • You’re evaluating investments in proptech companies, and need help navigating existing and future technologies and trends.

At the end of this seminar, you’ll:

  • Gain an understanding of the domain-specific data science methods for real estate
  • Recognize the possible benefits and applications of data science in real estate, how these techniques can support key business decisions, and be aware of potential challenges in implementation;
  • Learn how data science is proliferating in the industry, and gain an insight into the business models of disruptive new Proptech companies;
  • Know what to ask for from programmers and data scientists and better assess new data science hires or outsourced consultants;
  • Make more informed decisions related to collaboration or investment in data science startups or digital transformation initiatives.


Prerequisites: None   

Format: 2x2.5h seminar

Next Seminars:

December 1, 2020 - 8 AM GMT
December 2, 2020 - 8 AM GMT

Guest Speakers:
  • Topi Tiihonen, CEO of SkenarioLabs will introduce his Finland-based AVM company and talk about collaboration between institutions and startups - how to build trust, navigate the challenges of data sharing, and negotiate legal and "political" obstacles.
  • Clement Tien, CEO of Arical, will talk about his Hong Kong-based Geospatial AI startup, and discuss paths to monetization for data science in real estate, and the Asian business environment (willingness to pay for data and analytics, fundraising, and more).

Spaces are limited.
Register today to secure your spot.

February 17, 2021 - 8 PM EST
February 18, 2021 - 8 PM EST

Guest Speakers: TBA

Spaces are limited.
Register today to secure your spot.

Meet Your Lead Instructor

Nelson Lau, PhD, CFA

Nelson is the CEO of PropertyQuants Pte. Ltd., a PropTech startup bringing quantitative methods to global real estate. He has a PhD in Decision Sciences from INSEAD, is a CFA Charterholder, and completed his undergraduate work at Columbia University, double majoring in Economics and Mathematics-Statistics.

He has published papers in Management Science, Decision Support Systems, and Decision Analysis, one of which received a special recognition award. Nelson started his career as a trader/researcher at R G Niederhoffer Capital Management, an award-winning US hedge fund deploying systematic data-driven medium and low frequency strategies to global markets, and also spent significant time as lead trader at KCG, a leading global high frequency algorithmic trading firm.

He was also a Quantitative Macro Strategist at GIC and Managing Director at a proprietary trading firm (Acceletrade Technologies). Nelson has been investing in international residential real estate in a personal capacity for 10 years, and has a deep interest in bringing more systematic, quantitative, and data-driven approaches to real estate practice.

Interested in learning more?

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