COURS.

APERÇU

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

• Understand the crucial importance of data in the development of artificial intelligence, particularly regarding the role of data in model learning.
• Master basic techniques of descriptive statistics and their importance in data analysis for AI.
• Interpret and validate AI model results using statistical analysis methods to ensure model reliability and efficiency.

Description
This webinar aims to provide a deep understanding of the importance of data and statistical calculations in the field of artificial intelligence. Special attention will be given to basic techniques of descriptive statistics to analyze and interpret data effectively. We will also discuss how to visualize data to facilitate understanding and communication of results.

Finally, participants will learn to analyze and validate AI model results, a key skill to ensure the accuracy and usefulness of AI applications.

Who Should Attend
This session is ideally designed for professionals and engineers who wish to deepen their understanding of AI, while being accessible and beneficial for anyone interested in the practical application of artificial intelligence in various fields including:

• Chemical Engineering
• Civil Engineering
• Environmental Engineering
• General Engineering

Horaire : 12:00 PM - 1:30 PM EDT

Exigences techniques

Pour les utilisateurs de PC
OS: Windows 7, 8, 10 ou plus récent

Navigateur :
IE 11 ou plus récent, Edge 12 ou plus récent, Firefox 27 ou plus récent, Chrome 30 ou plus récent

Pour les utilisateurs de Macintosh
OS: MacOS 10.7 ou plus récent

Navigateur :
Safari 7+, Firefox 27+, Chrome 30+

iOS
OS: iOS 8 ou plus récent

Android
OS: Android 4.0 ou supérieur

voir le programme complet

PROGRAMME

Syllabus:

• Importance of data in AI
  - Role of data in model learning
  - Types of data: structured vs unstructured
  
• Basic statistical techniques for AI
  - Descriptive statistics
  
• Interpretation of results
  - Analysis and validation of model results

FORMATEUR

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

Hossein Bonakdari, Department of Civil 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.