Online Workshop 1 - Data Processing with Python for Geotechnical Engineers
Workshop Schedule: Sep 23, Sep 24, Sep 30 and Oct 1, 2020 - 11 AM to 4 PM EST/EDT
20 PDH Credits
In this twenty hour workshop, you will learn the basics of Python programming and how it can be used to facilitate quick and efficient processing of data files frequently used in engineering practice. Data processing with Python means getting things done faster, getting reliable results with fewer errors, while opening up a whole new world of possibilities for reporting, automated checks and interactive visualizations. While a seemingly daunting task at first sight, learning Python is a relatively easy task for engineers, who by default have had years of experience in algorithmic thinking.
LEAD THE WAY AND CHANGE OUR FIELD FOR THE BETTER!
Our first workshop will introduce you to the popular Python programming language, and no prior knowledge is required. We will start from the basics: numbers, strings, lists, dictionaries, if statements, for loops and functions, as well as NumPy, Pandas, and Matplotlib for data processing and plotting. You will also learn how to use Python to perform engineering calculations and work with common data files such as boring logs, PDF reports, CAD files and more.
WORKSHOP 1 - AGENDA
Sep 23, 2020 - 11 AM to 4 PM EST/EDT (5 hours):
● Programming environment setup (Jupyter notebook)
● Python basics: numbers, strings, indexing, slicing, lists, dictionaries, if statements, for loops and functions
Sep 24, 2020 - 11 AM to 4 PM EST/EDT (5 hours):
● Reading and writing data files (MS Excel, CSV, JSON, XML)
● Parsing and processing internet data, HTML web scraping
Sep 30, 2020 - 11 AM to 4 PM EST/EDT (5 hours):
● Working with common engineering data: boring logs, PDF reports, CAD files, etc.
Oct 1, 2020 - 11 AM to 4 PM EST/EDT (5 hours):
● Static plotting and interactive visualizations, geotechnical
● Setting up automated tasks and checks
Workshop Instructor: Nick Machairas, PhD,
Nick Machairas, PhD, is a geotechnical engineering and applied analytics consultant with more than seven years of experience building custom business and engineering AI solutions, thus minimizing risk and construction costs. He holds a PH.d from New York University in Civil Engineering. He is also a lecturer at Columbia University and New York University, where he teaches graduate courses on modern database systems and machine learning. He can be reached at
nick@machairas.com.
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