Discover how to transform raw support ticket data into actionable insights. In this module, you'll analyze TicketWise's ticket patterns and prepare data for modeling success. Through exploratory data analysis and systematic preprocessing, you'll uncover key insights about resolution times, customer segments, and routing patterns while ensuring data quality. Using Python libraries and AWS integration, you'll create a clean, well-structured dataset that will form the foundation of your routing solution.

Ready to turn your prepared data into predictive power? In this module, you'll build and evaluate machine learning models that automatically route TicketWise's support tickets. Through feature engineering, model development, and systematic evaluation, you'll create a solution that makes intelligent routing decisions. Using both traditional techniques and AI assistance, you'll learn to select the right models, measure their effectiveness, and document your approach for production deployment.

From automated pipelines to clear documentation, this module transforms individual ML components into a production-ready system. Using TicketWise's support ticket routing solution as a practical example, you'll learn to build automated data pipelines, deploy models in AWS SageMaker, create insightful visualizations, and generate comprehensive documentation. Through hands-on labs and real-world scenarios, you'll master the skills needed to turn promising models into valuable business solutions, using both traditional techniques and AI assistance to ensure your work is scalable, maintainable, and well-documented.