Data Mining and Analytics

This course enables students to acquire expertise in employing several techniques and tools for effective data mining. The course encompasses a comprehensive exploration of key topics such as clustering for targeted analysis, classification for outcome prediction, ranking algorithms for prioritization, and similarity search for information retrieval. Additionally, students delve into association rule mining to uncover meaningful relationships and anomaly detection for identifying irregular patterns.

The curriculum places a strong emphasis on practical applications, providing students with hands-on experience in refining analytic models. This practical approach enables proficiency in data analysis, pattern recognition, and decision support across diverse domains. By the end of the course, students will have the skills and knowledge to navigate the intricacies of data mining and analytics, making informed decisions in real-world scenarios.