AI-assisted coding for water modellers - On Demand Training

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Take sessions anytime, at your own pace with unlimited course access for 30 days on sign up.

This course introduces AI-assisted coding techniques to streamline and enhance hydrologic and hydraulic modelling workflows. Participants will learn to leverage tools like ChatGPT and AI-powered coding environments to efficiently manipulate model files, extract data, and automate complex tasks in water resources engineering and geospatial analysis. Through hands-on exercises and real-world applications, attendees will gain practical skills in applying AI to common challenges in hydrologic/hydraulic modelling. Join us to explore the cutting-edge intersection of AI and water resources engineering.

This 3-session course will delve into advanced topics such as HEC-RAS automation, including plan and unsteady file manipulation, 2D infiltration overrides, and parallel execution. Participants will gain expertise in extracting and visualizing data from HDF/DSS files, processing geospatial data, and accessing public climate data APIs. This course equips you with the skills to automate complex coding tasks using AI-driven tools in the context of water resource engineering.

Details

Format	3 x 2-hours recordings + course material and resources.
Cost	AUD $895.00 (INC GST)
Code	OD-25-3-120
Contact	training@awschool.com.au
Tags	Artificial Intelligence (AI) / Python / HEC-RAS

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Register your interest: https://awschool.com.au/training/ai-python-for-modellers/

Presenters

Bill Katzenmeyer

Fenstermaker

William Mark (Bill) Katzenmeyer, P.E., C.F.M. is Senior Water Resources Technical Lead for C.H. Fenstermaker and Associates, LLC. Bill specializes in hydrologic and hydraulic modeling, automation, a... Read more

Aaron Nichols

Atwell, LLC

Aaron Nichols is a water resources engineer at Atwell, LLC, specializes in 2D modeling with HEC-RAS and FLO-2D. He has worked on projects that include large-scale 2D urban modeling, design of regional... Read more

Sean Micek

Fenstermaker

Sean Micek, P.E. is a licensed Professional Engineer whose background is in hydrologic & hydraulic modelling, coastal transition zone analysis, and full-stack software development. Before joining ... Read more

Panel Members

Blake Marxsen

WMS Engineering

Blake Marxsen is a visionary environmental engineer with expertise in sustainability, hydrology, and AI-driven solutions. Growing up in the small coastal town of Binningup, Western Australia, Blake's ... Read more

Krey Price

International Water Training Institute

Educated at the University of California at Berkeley, Krey is a civil engineer and project manager with international experience in water resources. He is engaged in computational modelling, engineeri... Read more

Course Overview

This course provides a hands-on introduction to AI-assisted coding for water resources workflows covering ChatGPT integration, HEC-RAS automation, and advanced data processing techniques using Python. Attendees will gain practical skills in leveraging AI tools to streamline workflows, manipulate model files, and automate complex tasks in hydraulic engineering and geospatial analysis.

Learning Outcomes

Proficiency in using AI-assisted coding tools like ChatGPT and Cursor for efficient code generation and debugging in hydraulic modelling tasks.
Ability to automate HEC-RAS workflows, including file manipulation and parallel execution using AI-driven techniques.
Skill in extracting and processing hydrological data from various sources using Python and AI-assisted coding.
Competence in leveraging AI for GIS workflow automation and creating advanced visualizations for hydraulic modelling reports.

Course Outline

The course covers 3 main topics namely;

Session 1: Introduction to ChatGPT, Jupyter Notebook and AI-Assisted Coding Environment Cursor

When and how to use ChatGPT for coding.
ChatGPT for model data extraction and manipulation.
Copilot and Ctrl+K Code generation.
Managing Knowledgebase.
Basic examples of AI Code generation, debugging and iterating using existing code.

Session 2: HEC-RAS Automation using AI-Assisted Coding

Assembling prompts for code-based text file manipulation.
Plan and unsteady file manipulation.
Applying 2D infiltration overrides.
Parallel execution using HEC-Commander.

Session 3: Advanced Examples using Jupyter Notebooks

Extracting data from HDF/DSS (Time Series and Gridded Data).
AI for GIS workflow automation.
Creating report-ready charts and plots.
Geospatial data processing with whitebox tools.
API Access to public climate data.
Automating environment setup for portability using a custom GPT.

Format

3 session recordings available via the learning platform (LMS);
Unlimited course access for 30-days upon sign up;
Pre-and-post-course materials to go through via the LMS;
Exercises between the 3 sessions;
Ability to ask questions to the presenters at anytime through the LMS.

Pre-requisites

No prior experience with AI-assisted coding or ChatGPT is required, but basic familiarity with programming concepts is beneficial.
Working knowledge of setting up 1D and 2D HEC-RAS models.
Basic understanding of GIS concepts and data formats used in hydraulic modelling.
View the AWS Past webinars:
- AI tools for modelling innovation

- Applying AI to HEC-RAS Modelling Workflows

Requirements

A good internet connection and software and downloads as described in the learning platform.
A computer with Windows OS.

Completion Certification

Attendees earn CPD hours/points (i.e. with Engineers Australia) for at least 12 hours for the entire course.
On completion of the course attendees will be issued with a Certificate of Completion.

Refund Policy

Frequent Asked Questions (FAQs)