By the end of this course, students will have a solid understanding of how business analytics and artificial intelligence are used in business scenarios. The course introduces Python as a practical tool for data processing and analysis, starting from basic syntax and gradually moving toward more applied use cases. Students will learn how to collect, clean, and organize data using common libraries such as Pandas and NumPy, and how to explore and visualize data to support decision making. The course also introduces the basic ideas behind machine learning and shows how AI models can be applied to business problems using tools like Scikit-learn. Throughout the course, students will practice interpreting results, understanding model limitations, and thinking critically about how data and AI techniques can be used responsibly in business settings.

1. AI-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning 1st Edition, Tobias Zwingmann (Author), 2022.

2. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython 2nd Edition, William McKinney (Author), 2017.