Application of Artificial Intelligence in Civil/Environmental Engineering

Online /
Apr 15 - 17, 2025 /
Course Code: 15-0416-ONL25

The confirmation of this course depends on early registration; Register early to avoid the postponement or cancellation of a course.
  • Overview
  • Syllabus
  • Instructor


Please note, This instructor-led course has specific dates and times:
This course is held online over 3 days on the following schedule (All times in Eastern Time Zone):

10:00 am to 3:00 pm Eastern (includes a 30 minute lunch)

No knowledge of programming is required

After participating in this course, you will be able to:

  • Understand primary AI techniques
  • Know the basics of evaluation methodologies for Civil/Environmental Engineering problems
  • Get a working knowledge of how to apply AI technologies to real-world datasets
  • Gain experience designing and using AI techniques in Civil/Environmental engineering problems

Artificial intelligence (AI) techniques and machine learning approaches will revolutionize many aspects of the future Civil/Environmental Engineering field. AI can be a promising tool to tackle different problems, but related aspects of civil/environmental practical cases are a significant concern worldwide. The main focus of this course is to understand and discuss the recent developments in AI applications relating to practical engineering applications.

This course introduces various topics in AI approaches and learning methods in modelling and predicting complex environmental systems. The practical examples are illustrated and will show you how to apply this technique.

Course Outline:

  • Data acquisition/Preprocessing
  • Classification methods
  • Artificial Intelligence (AI) Modeling tools
  • Post-processing

Who Should Attend:
Civil and Environmental Engineers • Project Engineers and Managers • Consultants • Designers • Operation and Maintenance personnel • Developers • Planners

Special Features & Requirements

All codes are user-friendly, and trainees will be able to use them for their cases after this course. No knowledge of programming is required.

More Information

Time: 10:00 AM - 3:00 PM Eastern Time

Please note: You can check other time zones here.


Data acquisition and preprocessing

  • Gathering the data
  • Outliers detection
  • Transferring raw information into usable data
  • Splitting the data into training & testing sets.

Classification methods

  • Decision tree(DT)
  • M5 prime (M5’)
  • K-nearest neighbour algorithm (KNN)


  • Analysis of statistical indices
  • Scatter plot
  • Box plot

Artificial Intelligence (AI) Modeling tools

  • Multilinear regression (MLR)
  • Multivariate adaptive regression splines (MARS)
  • Multi-layer perceptrons (MLP)
  • Adaptive network-based fuzzy inference system (ANFIS),
  • Extreme learning machines (ELM)

Hands-on Projects in Civil and Environmental Engineering

Questions and Answers and Feedback to Participants on Achievement of Learning Outcomes


Hossein Bonakdari, Ph.D., P.Eng.

Hossein Bonakdari, Department of Civil Engineering Engineering, Ottawa University.

Hossein Bonakdari has worked for several organizations, most recently as a faculty member of the Department of Civil Engineering at the University of Ottawa, Ontario. He has supervised several Ph.D. and MSc students with teaching experience of more than 16 years in the field of Artificial Intelligence application in Civil and Environmental Engineering.

His fields of specialization and interest include the practical application of soft computing techniques in engineering problems. Results obtained from his research have been published in more than 300 papers in international journals (h-index=53). He has also had more than 150 presentations at national and international conferences. He published three books. Dr. Bonakdari's exceptional research achievements have garnered global recognition, consistently placing him in the top 2% of the world's top scientists across various fields for four consecutive years (2019-2023).

Dr. Bonakdari is currently leading several research projects in collaboration with industrial partners.

The Engineering Institute of Canada

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Course Rating
4.1 out of 5

Overall rating of this course by its previous attendees!

Fee & Credits

$1295 + taxes

  • 1.4 Continuing Education Units (CEUs)
  • 14 Continuing Professional Development Hours (PDHs/CPDs)
  • ECAA Annual Professional Development Points

Group Training
This course can be customized and delivered to your group of staff at your facility, saving time and money.
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