Online Workshop Series: Databases and Machine Learning for Engineers
The future of geotechnical engineering will pass through data analytics and machine learning. Firms that transform their information to meaningful data will gain competitive advantages. If one waits there is an increasing risk that they will be left years behind. We want geotechnical firms, big and small, to be at the forefront.
Small engineering firms are running the risk of getting marginalized by bigger competitors or by a market disruptor. Larger firms are likely sitting at a goldmine but they are not realizing its full potential.
The time to prepare is now!
This series of 3 online workshops, will equip you with the tools need for your business to thrive in this new challenging environment. Each of the workshops can be attended independently. Basic Python knowledge is required for our third workshop (on Machine Learning), which you can gain by also registering for our first workshop (on Data processing with Python).
Lead the way and transform our field for the better!
Advanced analytical methodologies based on artificial intelligence are disrupting one field after another and the geoprofession is next. This series of workshops will help you:
Be be more efficient in your everyday tasks
Organise and process vast amounts of geotechnical and engineering data
Augment your design skills
Apply Machine Learning in Geotechnical Engineering
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.
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.
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 (5 hours):
● Programming environment setup (Jupyter notebook)
● Python basics: numbers, strings, indexing, slicing, lists, dictionaries, if statements, for loops and functions
Sep 24, 2020 (5 hours):
● Reading and writing data files (MS Excel, CSV, JSON, XML)
● Parsing and processing internet data, HTML web scraping
Sep 30, 2020 (5 Hours):
● Working with common engineering data: boring logs, PDF reports, CAD files, etc.
Oct 1, 2020 (5 hours):
● Static plotting and interactive visualizations, geotechnical
● Setting up automated tasks and checks
Online Workshop 2 - Database Management Systems for Geotechnical Engineers
Workshop Schedule: Oct 27, Oct 28, Nov 4 and Nov 5, 2020 - 11 AM to 4 PM EST/EDT
20 PDH Credits
The role of databases in data analytics cannot be overstated; databases facilitate efficient, secure and accurate information storage and retrieval across multiple users and platforms. As such, proficiency in database design and knowledge of SQL programming are essential skills for the modern engineer. Databases are crucial in enabling organizations to shift from simply handling unstructured information to processing data and producing insights. As such, you will learn how to program in SQL and design your own relational databases which can then serve as the backbone of interactive visualizations and analyses.This course is designed to help you develop these skills.
In this twenty hour workshop, you will learn how to design simple relational databases and populate the databases with data. Next, you will learn the basics of the most popular query language, SQL to interact with both Sqlite and Postgres databases. Finally, you will use the databases you create to connect to powerful reporting platforms such as PowerBI, Tableau and Metabase with civil engineering and geotechnical applications.
By taking this course, you gain life-time access to the course’s Discourse server where you can post questions and browse for answers and advice from industry experts.
WORKSHOP 2 - AGENDA
Oct 27, 2020 (5 hours):
● Database environment setup
● Introduction to relational databases
Oct 28 2020 (5 hours):
● SQL programming: select statements, joins, aggregate functions
● Database design, typical civil engineering requirements, typical geotechnical attributes
Nov 4 (5 hours)
● SQL programming (continued)
● Importing and exporting data
Nov 5 (5 hours):
● Databases as a backend for PowerBI, Tableau and Metabase, applications in geotechnical engineering
● Extra: database operations with Python
Online Workshop 3 - Machine Learning Fundamentals for Civil Engineers
Workshop Schedule: Dec 2, Dec 3, Dec 9 and Dec 10, 2020 - 11 AM to 3 PM EST/EDT
16 PDH Credits
Prerequisites: Basic Pythod Programming Knowledge or Participation in Workshop 1
In this sixteen hour workshop, you will develop practical machine learning and data science skills. The course will cover theoretical basics of a broad range of machine learning concepts and methods with practical applications to sample engineering datasets. By the end of this course you should be able to describe the principal models used in machine learning and the types of problems to which they are typically applied, determine to which problems machine learning is applicable and which model or models would be most appropriate in each case and apply the principal models in machine learning to appropriate problems.
Machine Learning has revolutionized numerous fields and it can be an invaluable tool for engineers in producing safer and more economical designs. Think of Machine Learning as having the collective experience of countless capable professionals at your disposal.
You will learn the fundamentals of supervised, unsupervised and deep learning and how you can apply machine learning techniques using Python with scikit-learn and Tensorflow. We will then focus on applying Machine Learning in Geotechnical Engineering by presenting case studies and showcasing how predictive modeling can outperform traditional design. The main goal of this workshop is to introduce you to the tools that will allow you to produce your own models.
By taking this workshop, you gain life-time access to the course’s Discourse server where you can post questions and browse for answers and advice from industry experts.
WORKSHOP 3 - AGENDA
Dec. 2, 2020:
● Python environment setup
● Introduction to Machine Learning, civil engineering areas of applicatoin,
Dec. 3, 2020:
● Supervised learning algorithms: overview of regression and classification with examples in geotechnical engineering
Dec. 9, 2020:
● Supervised learning algorithms (continued)
● Unsupervised learning algorithms: overview of clustering with examples in civil engineering, slope stability, geotechnical modeling
Dec. 10, 2020:
● End-to-end Machine Learning project demonstration
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