المساعد الشخصي الرقمي

مشاهدة النسخة كاملة : Introduction to Machine Learning for Forecasting and Detecting Natural Disasters


ايه عاطف
02-04-2024, 12:41 PM
Training course - Workshop - Training program,
actual attendance - online
. The Gulf Strategic Center for Training and Development (GULF STD) has the honor of offering a course.
Introduction to Machine Learning for Forecasting and Detecting Natural Disasters

:Course Objectives


.o Understand the basics of machine learning algorithms and techniques
o Learn how to collect, preprocess, and analyze data related to natural disasters
.o Explore various machine learning models for forecasting natural disasters
.o Develop skills to assess the reliability and accuracy of machine learning predictions
.o Apply machine learning algorithms to real-world natural disaster scenarios
.o Gain insights into ethical considerations and challenges in using machine learning for disaster management


All courses are held in many Arab and foreign countries :
( Turkey - Egypt - Europe - America - Saudi Arabia - Morocco - Jordan - Malaysia - UAE - Sultanate of Oman - Bahrain - Kuwait )
Duration of courses: 5 days / 10 days ...
and diplomas: 1 month / 2 months / 3 months / 6 months / year
====================== ===
The cost of attendance includes :
• Reception to and from the airport .
• Training bag (scientific material - pens - papers - evaluations - attendance form).
• The participant receives a certificate of completion of the program in Arabic and English, accredited by the Gulf Strategic Center for Training and Development .
• Specialized lecturer .
• The five-star training hall .
• Coffee break and snacks .
You can book now. There is a discount and special prices for groups and ministries / agencies / government and private companies.

To send a technical and financial offer that includes all the details related to the training programs. We are honored to have you contact us :
Ms. Aya Atef
Mobile - Viber - Whatsapp / 00201000016576
Email / Aya@gulfstd. com
Website / www.gulfstd.com
WhatsApp link / wa.me/+0201000016576


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