Info

    General objective
The general objective of the Artificial Intelligence Fundamentals course is to provide students with a strong foundation in AI concepts, methodologies, and applications

    Specific objectives
» Understanding core AI concepts and terminology (history, evolution, impact; machine learning, neural networks, deep learning, natural language processing)
» Familiarization with AI techniques and algorithms (types of learning; regression, classification, clustering, prediction)
» Understanding the fundamental principles of machine learning and neural networks (supervised learning, neural network architecture, backpropagation, activation functions)
» Understanding data and its role in AI (sets of data, preprocessing, bias)
» Building and evaluating AI models (model selection, training and validation, evaluation metrics)
» Hands-on experience with AI tools and libraries (TensorFlow, Scikit-learn, Python-based AI development environments)
» Develop problem-solving and analytical thinking skills (map real-world problems to appropriate AI solutions)
» Ethics and social implications of AI (bias in AI models, responsible use, regulatory framework and policies, risks)