Introduction to Data Science Artificial Intelligence

In today's data-driven world, data has become a key driver of decision-making, provided it is handled, analysed, and interpreted correctly. This course introduces the core principles of Data Science, with emphasis on the full data pipeline, including data handling and cleaning, exploratory data analysis, data visualization and presentation, data-driven inference, and data-driven identication. Students will learn to work closely with data and make decisions guided by evidence rather than intuition, as well as communicate insights effectively through digital storytelling using both programming-based and industry-standard visualization tools such as Tableau. The course also introduces foundational concepts in Artificial Intelligence, including state space representation, uninformed search, and reinforcement learning. These topics are used to develop computational thinking and to provide students with an understanding of how machines reason and learn. Ethical issues in Data Science and Artificial Intelligence are discussed to raise awareness of their broader societal impact. Selected contemporary topics in Data Science and Artificial Intelligence will also be introduced to expose students to current developments in the field. Python is used throughout the course as the main programming language for hands-on learning.