Course Outcome

• Recall the key concepts, techniques, and algorithms used in data mining and their applications. 
• Understand the various data mining tasks (classification, clustering, regression) and their implementation using Python. 
• Apply Python libraries (such as Scikit-learn, Pandas, and Numpy) for implementing data mining algorithms.
• Analyze and preprocess data to extract useful information, handle missing values, and prepare data for mining. 
• Evaluate the performance of various data mining models using appropriate metrics and validation techniques. 
• Design and implement data mining projects, including classification, clustering, and regression models, to solve real-world problems.