Machine Learning with Statistics is a practical course designed to help learners build a strong foundation in machine learning by combining statistical concepts with real-world data analysis. The course introduces students to the fundamentals of machine learning and explains how statistics plays an important role in understanding data, identifying patterns, building models, and making reliable predictions.
Students will explore supervised learning in depth, focusing on two major areas: regression and classification. In regression, learners will understand how machine learning models can predict continuous values and explore commonly used regression algorithms. In classification, students will learn how models can categorize data into different classes and work with popular classification algorithms.
The course will also cover essential concepts such as data preparation, feature selection, model training, testing, prediction, and model evaluation. Students will learn how to interpret model performance using appropriate statistical and machine learning metrics and understand how to select the right algorithm for different business problems.
