Understanding the concept of artificial intelligence, its history of development, and its main branches.

Recognizing the role of data in artificial intelligence and how to analyze and prepare it.

Learning the basics of machine learning and deep learning and their applications.

Understanding natural language processing and computer vision techniques.

Grasping the concepts of generative artificial intelligence and AI agents.

Becoming familiar with expert systems, robotics, the Internet of Things, and cloud computing.

Addressing the ethical and regulatory challenges associated with artificial intelligence in line with international best practices.

Day 1: Fundamentals of Artificial Intelligence

• Concept of Artificial Intelligence and its history
• Main branches
• Key applications in daily life

Day 2: Data Science

• The role of data in Artificial Intelligence
• Stages of data analysis
• Data preparation
• Essential tools and techniques

Day 3: Machine Learning

• Concept of Machine Learning and its types
• Common algorithms
• Workflow (from data to model)

Day 4: Deep Learning

• Fundamentals of neural networks
• Training and its mechanisms
• Types of networks (CNN / RNN / Transformers)
• Applications

Day 5: Computer Vision + NLP

• Natural Language Processing (concepts + applications)
• Impact of deep learning on language understanding
• Computer Vision (tasks + techniques + applications)

Day 6: Modern and Advanced Technologies

• Generative Artificial Intelligence
• AI agents
• Expert systems

Day 7: Integration, Applications + Ethics

• Robotics and Internet of Things + Edge Computing
• Cloud computing, AR/VR, and the Metaverse
• Governance and ethics
• Privacy and risk management
• Case studies and practical applications