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1. Meet Your Instructor
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2. INTRODUCTION TO DATA SCIENCE
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3. Course Curriculum Overview
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4. INTRODUCTION TO R
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5. R Programming
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6. R Data Structure
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7. Import and Export in R
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8. Data Manipulation
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9. Data Visualization
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10. Introduction To Statistics
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11. HYPOTHESIS Testing -1
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12. Hypothesis Testing in Practice
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13. Machine Learning Toolbox
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14. Business Use Case Understaing
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Topic 14
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15. Data Pre-Processing
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16. SUPERVISED LEARNING REGRESSION
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17. Classification Overview
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17. Logistic Regression
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18. K-NN
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18. Logistic Regression
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19. K-NN
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19. SVM
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20. Naive Bayes
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20. SVM
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21. Decision Tree
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21. Naive Bayes
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22. Decision Tree
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22. Random Forest
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23. Capstone Project - Titanic Survival
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23. Random Forest
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23. Capstone Project - Titanic Survival
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24. Capstone Project - Titanic Survival
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24. K-Mean Clustering
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25. Hierarchical Clustering
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25. K-Mean Clustering
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26. DBScan Clustering
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26. Hierarchical Clustering
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27. DBScan Clustering
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27. Principal Component Analysis (PCA)
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28. Association Rule Mining
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29. Association Rule Mining
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29. Capstone Project - Big Mart Sell
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30. Capstone Project - Big Mart Sell
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30. Model Deployment
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31. Bonus Section - $997 Value Inside
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31. Model Deployment
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32. Bonus Section - $997 Value Inside