GCDAI - Global Certification In Data Science & AI
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01. GCDAI - Orientation Session (6th Jan 2024) (21:54)
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02. Campaign Return on Marketing Investment - Practice Set
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03. Introduction To Machine Learning (40:59)
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04. Machine Learning - Data Science & AI Perspective (93:56)
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05. Machine Learning - Linear Regression (171:30)
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06. Machine Learning - Linear Regression Practice Sets (88:44)
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07. Machine Learning - Practice Set Presentation by Team (110:34)
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08. Machine Learning - Introduction To Logistics Regression (157:54)
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09. Machine Learning - Logistics Regress Practice Set (Sales Prediction) (90:13)
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10. Machine Learning - Project Presentation on Linear & Logistic Regression By Team (115:04)
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11. Machine Learning - Decision Tree Classifier (116:55)
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12. Machine Learning - Decision Tree - Practice Set Presentation (99:58)
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13. Machine Learning - Random Forest Classifier (118:38)
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14. Machine Learning - Random Forest Classifier - Practice Project (110:36)
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15. Presentation By Team - Practice Sets (17:11)
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16. Random Forest - Practice Set Discussion & Presentation (42:13)
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17. Horse Survival Prediction - Random Forest ML - Class Discussion (17:31)
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18. Naive Bayes Classifier & Practiceset presentation (97:44)
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19. Naive Bayes Classifier - Presentation and Case Illustration (95:22)
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20. Naive Bayes - Team Presentation (81:44)
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21. KNN (K-Nearest Neighbor) ML Classifier (73:13)
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22. KNN Classifier - Project Assignment Team Presentation (60:39)
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23. K-Means Clustering - ML Algorithm (77:47)
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24. K-Means Clustering - Walmart Case Study (58:36)
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25. K-Means Clustering - Income Analyzer Team Presentation (46:46)
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26. Hierarchical Clustering - ML Algorithm (42:22)
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27. PCA - Dimensionality Reduction (86:03)
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28. PCA - Case Study Discussion & Build PCA using SkLearn (74:59)
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29. PCA - Project Assignment Presentation Discussion (33:31)
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30. Team Presentation on Image Detection Case Studies using PCA (56:42)
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31. Case Study Discussion - Uber Trip Prediction Case Study (10:04)
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32. Case Study Presentation by Team - PCR and Uber Case Studies (74:54)
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33. Introduction To Power BI - Reports Generation (145:34)
Machine Learning - Task Assignments & Practice Sets
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01. Companies Profit Prediction - Linear Regression ML
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02. Patient Diabetes Prediction - Logistic Regression ML
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03. IRIS Leaf Species Detection - Decision Tree ML
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04. Horse Survival Prediction - Random Forest ML
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05. Shopping Prediction - Naive Bayes Classifier
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06. Titanic Survival Prediction - Naive Bayes Classifier
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07. Uber Use Case - Build a ML Model to Predict Trip Duration
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08. Patient Diabetes Prediction - KNN Classifier
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09. Income Spent Analysis : K-Means Clustering
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10. Determine PCA : Covariance & Correlation Matrix, Eigen Vectors and Values
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11. Image Prediction Using PCA
Value Propositions
