Diploma Overview
The volume of aerial data being captured has exceeded the capacity of manual analysis, creating a need for professionals capable of building and applying artificial intelligence and machine learning workflows to extract value from this data.
This diploma prepares students to structure aerial datasets, apply machine learning and computer vision techniques to imagery and sensor data, and implement an AI-driven analytics project that addresses a defined industry problem—all built upon the same EASA-compliant aerial foundation shared across AAU's drone diplomas.
Course Learning Outcomes
- Prepare and structure aerial data for analytical and machine learning workflows.
- Apply machine learning techniques to aerial imagery and sensor data.
- Implement computer vision methods for automated object detection.
- Evaluate model performance and manage data quality.
- Execute an AI-driven analytics project that addresses a defined industry problem.
Main Diploma Structure (6 Courses)
#
Course Title
Objective
Theory
Practical
Total
1
EASA Open Category A1/A3 — Remote Pilot Fundamentals
Establishes the legal, safety, and aircraft-handling competencies required to operate drones within the Open Category (A1/A3 subcategories). Covers aviation law, airspace, human factors, meteorology, basic aircraft handling, and pre-flight risk assessment.
18
12
30
2
EASA Open Category A2 — Remote Pilot Competency
Builds on Course 1 to develop additional theoretical knowledge and operational competency associated with the A2 subcategory, including operations at closer distances, technical aircraft knowledge, and advanced risk mitigation.
24
16
40
3
Aerial Data Engineering and Pre-processing
Data workflows, cleaning, and structuring of aerial datasets for analysis.
36
54
90
4
Machine Learning for Aerial Data
Applied machine learning techniques and model training using aerial imagery and sensor data.
36
54
90
5
Computer Vision and Automated Object Detection
Computer vision workflows for automated detection, classification, and analysis.
36
54
90
6
AI-Driven Analytics Capstone Project
An integrated analytics/AI project addressing a real-world industry problem.
26
84
110
Target Groups - Data science, computer science, or engineering students seeking an applied specialization in artificial intelligence and drones.
- Technicians and analysts already working with aerial or geospatial data who seek formal training in machine learning and computer vision.
- Career-transitioning professionals with a programming or data background seeking to enter the drone sector.
Program Details - Duration: One Academic Year (300 Hours).
Location: AAU.
Start Date: 01/11/2026.
End Date: 01/08/2027.
Fees
Fees are determined in accordance with the university's approved financial policy.
Registration Procedures
Complete the program admission application.
Review by the Center for Consultation and Training.
Contact via extension numbers: 2590 / 2272.
Or by email: CCE@AMMANU.EDU.JO
