Applied Machine Learning

Service Description

An application-driven machine learning course focused on building end-to-end prediction systems across real-world domains. The course emphasizes how models are used in practice—covering data pipelines, feature engineering, model selection, evaluation, and deployment. You will work on core problem types such as classification and forecasting, applying them to high-impact use cases including credit risk, fraud detection, customer acquisition, and market risk in BFSI, as well as applications in insurance, consulting, and pharma. The focus is on translating machine learning models into reliable decision-making systems, with attention to interpretability, robustness, and business impact.