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About the Course

Machine Learning and Data Analytics for HSE Professionals II is a continuation of Machine Learning and Data Analytics for HSE Professionals course. It is designed to provide a comprehensive understanding of intermediate concepts of machine learning in the context of Health Safety and Environment (HSE) management. The course will equip participants with the knowledge and skills required to deploy advance learning machine models make informed decisions and effectively communicate results to stakeholders.


Using Orange software, participants will create advance predictive models which are essential in predicting and preventing incidents in organizations.

What you will learn

1) Fundamental concepts of advance machine learning models and its relevance in the field of HSE.
2)To deploy various advance machine learning models in HSE context
3)To create various advance predictive models using Orange.
4)To effectively select advance machine learning models on HSE datasets
5)To effectively deploy advance machine learning models on HSE datasets
6)To evaluate advance predictive models' performance

Certification
Certificates of successful completion will be awarded to trainees who have demonstrated competency and achieved at least 75% attendance.

Your Facilitator

Facilitators are nationally recognised HSE Practioners with many years of international industrial experience across various industries and preferred partners with Singapore Institution of Safety Officers.

Facilitators are nationally recognised HSE Practioners with many years of international industrial experience across various industries and preferred partners with Singapore Institution of Safety Officers.

Course Schedule

Machine Learning and Data Analytics for HSE Professionals II

Fee

$390 nett

Duration

8 Hours (Synchronous)

SDUs

8

Oct 17, 2024

Nov 21, 2024

9am - 6pm

Enjoy special course fee for group registration of 5 and above! 

UTAP funding of up to 50% for eligible NTUC members, capped at maximum $500 per year!
Click here to submit UTAP

Course Registration

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