IBPSAUSA

Python Programming for Energy Modelers – IBPSA-USA Education Committee

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Presenter(s):
Date of Recording:
07/14/2021
Short Description
This seminar focuses on outlining the process of acquiring data science skills for building performance analysts with little or no previous programming experience.
Long Description

The building industry is exploding with data sources that impact the energy performance of the built environment and health and well-being of occupants. Spreadsheets just don’t cut it anymore as the sole analytics tool for professionals in this field. This seminar focuses on outlining the process of acquiring data science skills for building performance analysts with little or no previous programming experience. An introduction to data science skills will be given in the context of the building life cycle phases. Participants will use large, open data sets from the design, construction, and operations of buildings to learn and practice data science techniques. Major technical topics include data loading, processing, visualization, and basic machine learning using the Python programming language, the Pandas data analytics and sci-kit learn machine learning libraries, and the web-based Colaboratory environment. In addition, the course will provide numerous learning paths for various built environment-related tasks to facilitate further growth.

THANK YOU TO OUR SPONSOR BAUMANN CONSULTING FOR THEIR SUPPORT.

Check out their website here: https://baumann-us.com/

Baumann Consulting, with offices in Washington, DC, Chicago, and Frankfurt (Germany) provides consulting services for sustainable and innovative building solutions for the U.S. and international markets.

Presenter: 

Clayton Miller, Assistant Professor – National University of Singapore

Clayton is an Assistant Professor at the National University of Singapore in the School of Design and Environment (SDE). He holds a Doctor of Sciences (Dr. sc. ETH Zurich) from the ETH Zürich, an MSc. (Building) from the National University of Singapore (NUS), and a BSc./Masters of Architectural Engineering (MAE) from the University of Nebraska – Lincoln (UNL). He is a former U.S. Fulbright Scholar to Singapore and a Walter Scott Jr. Scholar at UNL.

He teaches the edX course, Data Science for Construction, Architecture and Engineering.

Docs:
Tags:
Python, data, programming, data science, analytics, machine learning
Host:
Education Committee of IPSA-USA