- Mesterséges intelligencia (MI)

This page contains the full subject materials for Artificial Intelligence, including course-level topics, engineering workflows, and supporting notes. The subject is offered in Hungarian, covering a range of topics relevant to artificial intelligence in the context of autonomous systems.

Themes

• Introduction: Overview of artificial intelligence and its importance in the context of autonomous systems.
• Introduction to agents: Understanding the concept of agents and their role in artificial intelligence.
• Search algorithms: Exploring various search algorithms used in AI, such as depth-first search, breadth-first search, and A* search.
• Knowledge representation: Methods for representing knowledge in AI systems, including logic, semantic networks, and ontologies.
• Reasoning and inference: Techniques for reasoning and making inferences based on available knowledge.
• Machine learning: Introduction to machine learning concepts, including supervised learning, unsupervised learning, and reinforcement learning.
• Genetic algorithms: Understanding genetic algorithms and their applications in optimization problems.
• Fuzzy logic: Exploring fuzzy logic and its use in handling uncertainty in AI systems.
• Neural networks: Introduction to neural networks and their applications in deep learning.
• Convolutional neural networks: Understanding convolutional neural networks and their use in computer vision tasks.
• Recurrent neural networks: Exploring recurrent neural networks and their applications in natural language processing.
• Transformers: Introduction to transformer models and their impact on natural language processing.
• Large language models: Understanding large language models and their applications in various AI tasks.