Artificial intelligence and data analytics provide the power to analyze and learn about large amounts of data from multiple sources and detect patterns to make future trend predictions. The education industry benefits from predictive analytics to make classroom teaching and learning decisions, school management and policy making. Hence, this course aims to introduce students to the foundational concepts of data analytics and their use in AI, to enable students to gain the background knowledge necessary to understand and develop different algorithms in AI and data analytics, and the concepts of data-driven decision-making and their use in AI.

CILO-1: Utilize skills in data collection, cleaning, and visualization techniques relevant to educational data. CILO-2: Apply predictive analytics models to address educational challenges (such as student performance prediction and dropout prevention). CILO-3: Develop data analytics skills to enhance teaching and learning and to inform administrative decisions. CILO-4: Analyze the ethical and societal implications of integrating AI and data analytics into education.