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# Data Mining Algorithms in SSAS, Excel, and R

### Course Summary

Don't use data mining as a black box. Get a deep understanding of how the data mining algorithms work. This knowledge is not only theoretical; it helps you developing better models in production.

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### Course Syllabus

Introduction to Data Mining
- 31m 0s

â€”Introduction and Modules 2m 5s
â€”Assumptions and Overview 0m 53s
â€”What Is Data Mining? 1m 34s
â€”Data Mining Types and Tasks 2m 18s
â€”Demo: SQL Server Queries 2m 0s
â€”Demo: SSRS Report 2m 23s
â€”Virtuous Cycle and CRISP Model 1m 44s
â€”Data Flow 1m 24s
â€”Types of Analyses and SQL Server Tools 2m 12s
â€”Demo: SSAS Cube 6m 37s
â€”Demo: Data Mining Model 4m 52s
â€”Excel Tools and R 2m 4s
â€”Summary 0m 50s
Naive Bayes and Decision Trees
- 34m 39s

â€”Introduction 0m 30s
â€”Naive Bayes Prior 2m 27s
â€”Naive Bayes Posterior 2m 25s
â€”Example and Usage 1m 31s
â€”Demo: Naive Bayes in SSAS 4m 41s
â€”Demo: Naive Bayes in Excel 3m 35s
â€”Demo: Naive Bayes in R 5m 45s
â€”Decision Trees 1m 59s
â€”Decision Trees Example 1m 40s
â€”Decision Trees Example and Usage 2m 40s
â€”Demo: Decision Trees in SSAS 2m 56s
â€”Demo: Decision Trees in Excel 2m 7s
â€”Demo: Decision Trees in R 1m 44s
â€”Summary 0m 34s
Linear Regression, Regression Trees, and Support Vector Machines
- 20m 48s
Linear Regression, Neural Network, and Models Evaluation
- 26m 19s
Time Series
- 24m 36s
Clustering
- 17m 36s
Association Rules and Sequence Clustering
- 24m 42s

Course Fee:
USD 29

Self-Study

### Course Status:

Active

1 - 4 hours / week

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