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In this live lecture screencast, we introduce data preprocessing and transformation. About 2024/25 CSC 4792: Data Mining and Warehousing Data Mining and Warehousing are critical for extracting actionable insights from large datasets. This course will cover the fundamental Data Mining techniques (classification, clustering, association rules) and explore data warehousing architectures (OLAP, ETL, star schema). The course will aligns with Information Management, Intelligent Systems, and Data Analytics. Data mining and warehousing prepare students for careers in Big Data, Business Intelligence, and artificial intelligence and machine learning. Learning Outcomes Explain data mining and data warehousing concepts, applications, and challenges Preprocess data (cleaning, transformation, reduction) Implement data mining algorithms (classification, clustering, association rules) Design a data warehouse (ETL, OLAP, star schema) Evaluate data mining models (accuracy, precision, scalability) Apply data mining and data warehousing tools (Python, Weka, RapidMiner) Discuss ethical issues (privacy, bias in DM) About the Live Lecture Recordings These were live and unscripted sessions, so---for posterity---please do share comments/fixes in the comment box if you spot an error or something that might require clarification. Video recording/screencasting was done using ffmpeg [3] and SmartRecorder [4] on a OnePlus 3T connected with a Boya BY-M1 microphone [5]. [1] https://moodle.unza.zm/course/edit.ph... [2] http://www.unza.zm [3] https://www.ffmpeg.org [4] https://play.google.com/store/apps/de... [5] http://www.boya-mic.com/lavaliermicro...