2025-10-13

General Information

• Standard course duration: 15 hours (unless otherwise stated).
• Mode of delivery: Onsite at NARSS Cairo or Online.
• Training delivered by experienced trainers with both academic and practical backgrounds.
• Limited seats to ensure quality instruction and hands-on practice.
• Priority registration for early payment.
• For registration & inquiries: WhatsApp +201009577573

Course Overview

Course description: Introduces machine learning (ML) techniques for remote sensing applications, including supervised, unsupervised and reinforcement learning concepts and their use for land cover classification, object detection and change detection.
Suggested duration: 4 weeks (customizable).

Prerequisites

• Introduction to Remote Sensing

• Introductory Statistics

Textbooks / References

• Goodfellow, I., Bengio, Y., & Courville, A. Deep Learning. MIT Press, 2016.

• Amini, B., & Amini, S. Machine Learning for Remote Sensing. CRC Press, 2018.

Course Outline

• Module 1: Introduction to machine learning

• Module 2: Supervised learning

• Module 3: Unsupervised learning

• Module 4: Reinforcement learning (overview)

• Module 5: Land cover classification

• Module 6: Object detection

• Module 7: Change detection

• Module 8: Case studies

Delivery & Assessment

• Interactive lectures, videos, and demonstrations

• Three homework assignments

• Group project (2-3 students)

• Periodic Q&A sessions

Learning Outcomes

• Understand core ML algorithms and apply them to remote sensing data.

• Develop an applied ML project addressing a real remote sensing problem.

Contact Information

Address: 23 Joseph Tito St., El Nozha El Gedida, Cairo, Egypt (Behind Cairo Airport)
P.O. Box: 1564 Alf Maskan, Postal Code: 11769
Phone: +20 2 26251202 / 26251203 / 26225836 | Fax: +20 2 26225800
Email: narssco@narss.sci.eg
WhatsApp (for registration & inquiries): +201009577573