Nid: 26203 Presentation Goals Requirements Syllabus Methodology Academics Syllabus Week 1 Introduction to artificial intelligence, context, and ethics. Data exploration and descriptive statistics. Programming tools for data manipulation and visualization. Development and presentation of a project using open data. Week 2 Introduction to machine learning. Supervised, unsupervised, and reinforcement learning. Formulation and design of a machine learning-based project. Trends in artificial intelligence, generative AI. Final project presentation.
