Fundamentals of Machine Learning and Artificial Intelligence Lecturer: Professor Dr. Ghada Mohamed Amer Artificial Intelligence Expert - Information and Decision Support Center, Cabinet In this course, you will learn the fundamentals of machine learning (ML) and artificial intelligence (AI). You will explore the connections between AI, machine learning, deep learning, and the emerging field of generative AI. You will gain a solid understanding of key AI terminology, paving the way for deeper exploration of these concepts. You will also gain practical insights into how to use these tools to solve real-world problems and drive innovation across various sectors. Course Level: Introductory Duration: 2 hours Description: Identifying the similarities and differences between artificial intelligence (AI), machine learning, deep learning, and generative AI Objectives: Define key terms and concepts in AI and machine learning. Explain the different data types used to train AI models. Define supervised learning, unsupervised learning, and reinforcement learning. Define neural networks. Define key terms and concepts in generative AI. Describe the basic model lifecycle. Define three main types of basic models: large language models, diffusion models, and multimodal models. Target Audience: Individuals interested in machine learning and AI, regardless of their specific job title.