Artificial intelligence and its applications

Explore the programs and courses offered by Artificial intelligence and its applications

Browse Programs Admission Information

Program Overview

Global Objective of the Doctoral Project


The overarching goal of this doctoral project is to leverage advanced artificial intelligence (AI) techniques to address pressing societal challenges across several strategic domains. It covers diverse PhD research areas, including AI-based hate speech detection, medical image analysis, early heart disease prediction, intelligent agricultural diagnostics, cybersecurity within Internet of Things (IoT) environments, mental health diagnostics, intelligent stress detection systems, and fake news identification.

The project utilizes cutting-edge AI methodologies—such as deep learning, large language models (LLMs), and computer vision—to foster technological innovation and create tangible societal impact.

Practically, the project aims to provide both theoretical frameworks and applied solutions to improve the operations of the Emergency Medical Aid Service (SAMU) and the Algerian Civil Protection, with a focus on responder health and communication efficiency in critical situations.

In agriculture, the goal is to integrate Agriculture 4.0 technologies to boost productivity through customized solutions spanning all stages—from land preparation to post-harvest processes.

This interdisciplinary approach aligns with the visions of Industry 4.0 and University 4.0 by promoting the adoption of smart technologies, fostering cross-disciplinary collaboration, and contributing to human and social development. By tackling challenges related to Information and Communication Technology (ICT) and digitalization, reducing biases, and promoting safer, more inclusive environments, the project contributes to the digital transformation of key sectors such as healthcare, agriculture, and information security.

Teaching Language : English

Curriculum Highlights

Core Courses


During the initial years of training, the doctoral student is required to take core courses that support their scientific research and provide them with modern methodological and technical tools. These core courses include:


Artificial Intelligence

Concepts and techniques of AI, machine learning, deep learning, and intelligent algorithms.

Deep Neural Networks Modeling

Design and training of neural networks with applications in computer vision and language processing.

Data Analytics & Data Science

Techniques for collecting, cleaning, and analyzing big data and extracting knowledge.

Research Methodology & Thesis Writing

Skills for preparing research projects, analyzing results, and academic publishing.

AI Ethics & Societal Impact

Issues of privacy, algorithmic biases, and the ethical responsibilities of researchers.

Cybersecurity in Smart Systems

Concepts of information security and data protection in IoT and intelligent systems.

Multidisciplinary AI Applications

AI applications in health, agriculture, public services, and emergency response.

 

 

Advanced Topics

Artificial Intelligence and Deep Learning

Generative Models

Explainable AI (XAI)

Real-Time Deep Learning

Reinforcement Learning

AI in Healthcare

Disease diagnosis using medical imaging

Mental health tracking through behavior and language analysis

Early detection of heart disease and diabetes using AI

Computer Vision and Image Processing

Automated image and video recognition

Medical and industrial image processing

Object tracking and motion analysis

Natural Language Processing

Large Language Models (LLMs)

Discourse analysis and hate speech detection

Real-time machine translation and sentiment analysis

Cybersecurity and Artificial Intelligence

Malware detection using machine learning

Protecting Internet of Things (IoT) infrastructures

Identity verification using digital fingerprints

Smart Agriculture and Agriculture 4.0

Use of drones and AI for crop analysis

Predictive modeling for agricultural yield

Precision and data-driven farming

AI in Emergency Services and Civil Protection

Smart support systems during disasters

First responder behavior analysis

Smart communication and data analysis in the field

Admissions Information

Language of Instruction: English is the primary language for training and research. Proficiency in French and Arabic is plus

Admission Requirements :

  • A Master’s degree in Computer Science or related fields (Artificial intelligence, data science, intelligent systems...)
  • An academic file including transcripts and a Master’s degree certificate
  • A preliminary research proposal or idea aligned with the project’s themes
  • An updated academic Curriculum Vitae (CV)
  • A motivation letter outlining research interests and objectives

Selection Process: File evaluation and remote interview if necessary

Duration of Study: 3 to 5 years depending on research progress

Supervision: Direct supervision by specialists in Artificial Intelligence

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