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| Lecture-17: Handling Time Series data |
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| Lecture-15: Revision |
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| Lecture-14: Project 1-slide presentations |
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| Lecture-12: Project details, KNN, WEKA demo |
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| Lecture-11: In-class business case competition |
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| Lecture-10: Case Study-2 Presentations |
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| Lecture-9: Decision trees and class exercises |
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| Lecture-8: Linear Regression |
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| Lecture-7: Case Study-1 Presentations |
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| Lecture-6: Data Quality, Eigenvalues, Eigenvectors, Principal Component Analysis |
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| Lecture-5: Case Study-1 Description; Data Quality |
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| Lecture-4: Data preprocessing, Seaborn for visualization, in-class case study |
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| Lecture-3 Recording Check Piazza announcements for more details. |
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| Lecture-3: Data preprocessing, Pandas |
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| Lecture-2 Recording Check Piazza announcements for more details. |
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| Lecture-2: Python Loops, Conditionals, functions, packages |
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| Lecture-1 Recording Check your email or blackboard announcements for the password. |
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| Lecture-1: Introduction to Data Mining and Python Basics |
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