Data Science Essentials: AI & Analytics

Master the data pipeline and analytics used in AI solutions. Covers data collection/storage (basic SQL), data cleaning and wrangling, exploratory analysis, and machine learning fundamentals. Students learn to transform raw data into insights using Python (pandas, NumPy) and create visualizations. The course also covers introductory statistics and supervised/unsupervised learning. A capstone mini-project (e.g. analyzing healthcare or logistics data) lets students apply AI models to a real-world scenario. Graduates will be prepared to take on data-driven roles or support AI initiatives in their organizations.