Implement Machine Learning Using Oracle Data Miner Course Overview

Implement Machine Learning Using Oracle Data Miner Course Overview

The "Implement Machine Learning Using Oracle Data Miner" course is designed to provide learners with comprehensive training on utilizing Oracle Data Miner for effective machine learning. The course begins with an overview that sets the stage for the training. It then dives into the Oracle Data Miner fundamentals, teaching participants essential concepts and techniques in two parts. Learners are introduced to the different user interfaces of Oracle Machine Learning, with practical sessions to solidify their understanding.

Subsequent modules cover the application of various machine learning models, including classification, regression, clustering, and anomaly detection, each with dedicated lessons and hands-on practices. For example, learners will practice with real-world datasets like the Titanic passenger data, Boston Housing data, and more, learning how to prepare data, create models, and interpret results using Oracle Data Miner.

By the end of the course, participants will have gained practical experience in machine learning workflows and model creation, making them equipped to leverage the power of Oracle Data Miner in their professional roles.

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  • Live Online Training (Duration : 24 Hours)
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  • Live Online Training (Duration : 24 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

You can request classroom training in any city on any date by Requesting More Information

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Course Prerequisites

To ensure you gain the maximum benefit from the Implement Machine Learning Using Oracle Data Miner course, it is important that you have the following minimum prerequisites:


  • Basic understanding of database concepts, including relational databases and SQL.
  • Familiarity with data processing and manipulation tasks, such as querying databases and data cleaning.
  • Some exposure to basic statistical concepts and machine learning algorithms, though in-depth knowledge is not required.
  • Experience with Oracle Database environments and tools, particularly SQL Developer, as the course involves practical exercises using these platforms.
  • A willingness to engage in hands-on practice and a keen interest in learning how to apply machine learning techniques using Oracle Data Miner.

Please note that while these prerequisites are aimed at ensuring a smooth learning experience, we encourage all interested learners to participate, as the course is designed to accommodate varying levels of prior knowledge. Our expert instructors will guide you through the foundational concepts and provide support as you progress through the more advanced material.


Target Audience for Implement Machine Learning Using Oracle Data Miner

  1. This course provides comprehensive training on Oracle Data Miner for implementing machine learning solutions.


  2. Target Audience for the "Implement Machine Learning Using Oracle Data Miner" course:


  • Data Scientists
  • Data Analysts
  • Business Intelligence Professionals
  • Database Administrators
  • Data Engineers
  • Machine Learning Engineers
  • IT Professionals working with data warehousing and analytics
  • Oracle Database Users looking to leverage machine learning capabilities
  • Professionals seeking to use Oracle Machine Learning for predictive analytics
  • Research Scientists (in a data-heavy environment)
  • Software Developers interested in data mining and machine learning
  • Students in computer science or related fields with a focus on data analysis and machine learning


Learning Objectives - What you will Learn in this Implement Machine Learning Using Oracle Data Miner?

Introduction to the Learning Outcomes

This course provides comprehensive training in Oracle Data Miner, focusing on developing skills to implement machine learning models and interpret data-driven insights effectively.

Learning Objectives and Outcomes

  • Understand the core principles and concepts of Oracle Machine Learning, including its architecture and data processing capabilities.
  • Gain proficiency in using Oracle Machine Learning User Interfaces to access, manipulate, and analyze data within Oracle databases.
  • Learn to establish a connection with SQL Developer and install the Data Miner Repository for Oracle Machine Learning workflows.
  • Develop the skills to create, evaluate, and interpret classification models, using datasets such as the Titanic survival data.
  • Master the process of data transformation and selection of variables using Attribute Importance for building machine learning models.
  • Acquire the ability to construct and apply regression models, utilizing real-world data like the Boston Housing dataset for predictive analysis.
  • Explore and implement clustering models to uncover hidden patterns and groupings within datasets, including the use of K-Means clustering.
  • Investigate the use of anomaly detection models to identify outliers and unusual patterns in complex datasets such as auto insurance claims.
  • Compare and contrast different machine learning models, including automated Oracle Machine Learning (OML) methods, for optimized performance.
  • Learn best practices for deploying machine learning models and integrating insights into decision-making processes within an organization.