Oracle Database 11g Data Mining Techniques Course

Oracle Database 11g: Data Mining Techniques Training

In this course, students review the basic concepts of data mining and learn how leverage the predictive analytical power of the Oracle Database Data Mining option by using Oracle Data Miner 11g Release 2. The Data Miner GUI provides intuitive tools that help you to explore the data graphically, build and evaluate multiple data mining models, apply Oracle Data Mining models to new data, and deploy Oracle Data Mining's predictions and insights throughout the enterprise.

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Oracle Database11g Data Mining UpComing Batches

Nov-29 - Jan-10

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Timings: 07:00 AM To 10:00 AM (IST)

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Nov-22 - Jan-03

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Dec-11 - Jan-22

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Dec-18 - Jan-29

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Dec-25 - Feb-05

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Jan-01 - Feb-12

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Timings: 20:30 PM To 23:30 PM (IST)

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Course Curriculum

Oracle Database 11g: Data Mining Training

SELF PACED

In this course, students review the basic concepts of data mining and learn how leverage the predictive analytical power of the Oracle Database Data Mining option by using Oracle Data Miner 11g Release 2. The Data Miner GUI provides intuitive tools that help you to explore the data graphically, build and evaluate multiple data mining models, apply Oracle Data Mining models to new data, and deploy Oracle Data Mining's predictions and insights throughout the enterprise.

  • WEEK 5-6
  • 10 Modules
  • 6 Hours
Course Content


Topics:
  • Suggested Course Pre-requisites.
  • Suggested Course Schedule.
  • Review Location of Additional Resources (Including ODM and SQL Developer Documentation and Online Resources).
  • Practice and Solutions Structure.
  • Class Sample Schemas.
  • Course Objectives.


Topics:
  • Why use Data Mining?
  • Examples of Data Mining Applications.
  • Supervised Versus Unsupervised Learning.
  • Supported Data Mining Algorithms and Uses.
  • What is Data Mining?


Topics:
  • Common Tasks in the Data Mining Process.


Topics:
  • Data Mining with Oracle Database.
  • Introducing the SQL Developer Interface.
  • Previewing Data Miner Workflows.
  • Examining Data Miner Nodes.
  • Identifying Data Miner Interface Components.
  • Setting up Oracle Data Miner.
  • Accessing the Data Miner GUI.


Topics:
  • Adding a Data Source to the Workflow.
  • Examining Class Build Tabs.
  • Creating Classification Models.
  • Comparing the Models.
  • Building the Models.
  • Reviewing Classification Models.
  • Selecting and Examining a Model.
  • Using the Data Source Wizard.


Topics:
  • Building the Models.
  • Performing Data Transformations.
  • Using the Data Source Wizard.
  • Adding a Data Source to the Workflow.
  • Selecting a Model.
  • Reviewing Regression Models.
  • Comparing the Models.
  • Creating Regression Models.


Topics:
  • Creating an Association Rules Model.
  • Creating a New Workflow.
  • Reviewing Association Rules.
  • What is Market Basket Analysis?
  • Adding a Data Source to th Workflow.
  • Building the Model.
  • Defining Association Rules.
  • Examining Test Results.


Topics:
  • Comparing Model Results.
  • Defining and Building Clustering Models.
  • Adding Data Sources to the Workflow.
  • Defining Output Format.
  • Describing Algorithms used for Clustering Models.
  • Examining Cluster Results.
  • Selecting and Applying a Model.
  • Exploring Data for Patterns.


Topics:
  • Building the Model.
  • Creating the Model.
  • Reviewing the Model and Algorithm used for Anomaly Detection.
  • Adding Data Sources to the Workflow.
  • Examining Test Results.
  • Evaluating Results.
  • Applying the Model.


Topics:
  • Requirements for Deployment.
  • Deployment Tasks.
  • Examining Deployment Options.

Program Syllabus

Curriculum

You can also view the program syllabus by downloading this program Curriculum.

Course Description

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Instructor-led Sessions

30 Hours of Online Live Instructor-Led Classes.
Weekend Class : 10 sessions of 3 hours each.

Real Life Case Studies

Real-life Case Studies

Live project based on any of the selected use cases, involving implementation of the various real life solutions / services.

Assignments

Assignments

Each class will be followed by practical assignments.

24 x 7 Expert Support

24 x 7 Expert Support

We have 24x7 online support team to resolve all your technical queries, through ticket based tracking system, for the lifetime.

Certification

Certification

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