The course is divided into two main segments. The first part focuses on building a strong foundation with topics like data preprocessing, exploratory data analysis (EDA), and introductory machine learning techniques. This prepares you for the more advanced content, which includes deep learning, NLP, big data analytics, and time series forecasting. The course culminates in a Capstone Project, where you will apply everything you’ve learned to solve a real-world problem, from model building to deployment.