This course provides a foundational introduction to Data Science and Artificial Intelligence (AI). Students learn core mathematical concepts such as descriptive statistics and probability and develop practical skills in data collection, preprocessing, visualization, and feature engineering. These skills lead to the development and implementation of machine-learning algorithms for data-driven decision-making across various applications. Through a mix of interactive lectures and guided labs, students gain hands-on experience with industry-standard tools and techniques commonly used in the field. TARGET AUDIENCE: Final-year computer-science undergraduates or Master’s applicants seeking a solid foundation in Data Science and AI, data analysts and IT professionals aiming to upskill in AI-driven methods PREREQUISITES: Introduction to Programming

Target Audience :
Final-year computer-science undergraduates or Master’s applicants seeking a solid foundation in Data Science and AI, data analysts and IT professionals aiming to upskill in AI-driven methods