BNAN420

043644

This course is designed to provide students with a comprehensive understanding of key concepts in descriptive statistics, data visualization, and machine learning. It covers essential techniques like regression, probability distributions, and time series analysis, along with practical applications in feature engineering, clustering, and segmentation. Students will gain hands-on experience with model training, testing, hyperparameter tuning, and model deployment using tools like PyCaret, Scikit-Learn, and AutoML frameworks. By the end of the course, learners will be equipped to analyze data, build predictive models, and implement machine learning pipelines to solve real-world business problems.

GRD - Regular Grades A, B, C, D, E

Undergraduate

019615