Artificial Intelligence

This course provides an essential introduction to Artificial Intelligence (AI), focusing on its theoretical foundations, practical applications, and societal relevance. The aim of the course is to equip learners with a comprehensive understanding of the core principles of AI, including its key paradigms such as symbolic reasoning and machine learning, as well as its technical and ethical implications. Designed for a broad audience, the course is suitable Pre-graduate, post-graduate and senior IT Programmers (should understand basic probability, statistics, algebra and calculus. should have some background in IT programming, and it would be helpful if they are familiar with Python.). Throughout the course, learners will develop fundamental knowledge of AI systems and the ability to apply this understanding to real-world problems. They will gain practical skills in programming and in the design of simple AI-based models, while also learning to critically assess the limitations and implications of these technologies. A key emphasis of the course is on the deep tech elements underpinning AI, such as data-driven algorithms, neural networks, and basic machine learning techniques. The course is structured around several key modules, covering topics such as the history and evolution of AI, core AI paradigms, an introduction to machine learning, basic neural networks, AI programming with Python, real-world case studies, and the ethical considerations surrounding AI use. Learners will engage with both theoretical content and practical exercises, including lab work, coding projects, and case discussions. The course is delivered through a combination of lectures, interactive tutorials, and hands-on sessions, and is assessed through quizzes, assignments, and a final project and exam.