Oracle Database 19c: Data Mining Techniques
The Oracle Database 19c: Data Mining Techniques course covers the basic concepts and primary terminologies associated with data mining. The course explains the steps associated with the data mining process, the use of Oracle Data Miner to perform data mining, and the options for deploying data mining predictive results.
STUDENTS WILL LEARN TO
- Create a User Account for Data Miner in Your Database
- Create a Data Miner User Connection
- Install the Data Miner Repository
- Create a Data Miner Project and Workflow
- Create Classification Models
- Create Regression Models
- Create Clustering Models
- View Model Results and Applying the Model
- Create an Association Rules Model
- Modify the Source Data and Rebuilding the Model
- Apply Model Rule Filters
- Create an Anomaly Detection Model

Phone
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Phone
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Product
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Oracle
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Code
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D1101944GC10
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Duration
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2 Days
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Price (baht)
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39,200
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About the course
COURSE OUTLINE
MODULE 01 Introduction
- Introduction
MODULE 02 Data Mining Concepts and Terminology
- Data Mining Concepts and Terminology
MODULE 03 The Data Mining Process
- The Data Mining Process
MODULE 04 Introducing Oracle Data Miner
- Introducing Oracle Data Miner
- Practice 3-1: Creating a User Account for Data Miner in Your Database
- Practice 3-2: Creating a Data Miner User Connection and Installing the Data Miner Repository
- Practice 3-3: Creating a Data Miner Project and Workflow
MODULE 05 Using Classification Models
- Using Classification Models
- Practice 4-1: Selecting and Examining Source Data
- Practice 4-2: Creating Classification Models
- Practice 4-3: Scoring the Data
MODULE 06 Using Regression Models
- Using Regression Models
- Practice 5-1: Creating a New Workflow and Examining the Source Data
- Practice 5-2: Creating Regression Models
- Practice 5-3: Scoring the Data
MODULE 07 Using Clustering Models
- Using Clustering Models
- Practice 6-1: Creating Clustering Models
- Practice 6-2: Viewing Model Results and Applying the Model
MODULE 08 Performing Market Basket Analysis
- Performing Market Basket Analysis
- Practice 7-1: Creating a New Workflow and Examining the Source Data
- Practice 7-2: Creating an Association Rules Model
- Practice 7-3: Modifying the Source Data and Rebuilding the Model
- Practice 7-4: Applying Model Rule Filters and Creating Model Details
MODULE 09 Performing Anomaly Detection
- Performing Anomaly Detection
- Practice 8-1: Creating an Anomaly Detection Model
- Practice 8-2: Viewing Model Results and Applying the Model
MODULE 10 Deploying Data Mining Results
- Deploying Data Mining Results
- Practice 9-1: Creating a Table for Data Mining Results
- Practice 9-2: Deploying the SQL Code for Data Mining Results
- Practice 9-3: Modifying Classification Models and Redeploying the Code
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