Predictive Analytics using Oracle Data Mining Course Overview

To ensure a successful learning experience in the Predictive Analytics using Oracle Data Mining course, the following prerequisites are recommended:

• Basic understanding of database concepts and familiarity with SQL (Structured Query Language).
• Knowledge of Oracle Database fundamentals, including the ability to navigate through the database and execute basic queries.
• An introductory-level comprehension of statistics and data analysis techniques.
• Familiarity with data warehousing principles and practices.
• Basic understanding of machine learning concepts, including supervised and unsupervised learning.
• A general awareness of business analytics and its importance in decision-making processes.

Please note that these prerequisites are meant to provide a foundation for the course material and are not intended to discourage anyone from enrolling. Individuals with a strong desire to learn and a willingness to engage with the course content may overcome any gaps in knowledge through dedicated study and practice.

Target Audience for Predictive Analytics using Oracle Data Mining

This course offers a deep dive into predictive analytics using Oracle Data Mining, tailored for IT professionals keen on data science.

• Data Scientists
• Data Analysts
• Business Analysts
• BI (Business Intelligence) Professionals
• Database Administrators
• Data Warehouse Specialists
• IT Professionals interested in data mining and analytics
• Oracle Database Professionals
• Machine Learning Engineers
• Software Developers with a focus on data analysis and mining
• Research Analysts
• Statisticians
• Information Systems Managers
• Technical Consultants specializing in Oracle databases
• Data Mining Practitioners

Learning Objectives - What you will Learn in this Predictive Analytics using Oracle Data Mining?

Introduction to the Learning Outcomes:

This course offers a comprehensive understanding of predictive analytics using Oracle Data Mining, focusing on key concepts, processes, and practical applications in data mining with Oracle's tools.

Learning Objectives and Outcomes:

• Understand the fundamentals of predictive analytics and data mining, and their applications in real-world scenarios.
• Learn to use Oracle Advanced Analytics (OAA) to apply predictive analytics within Oracle's database environment.
• Differentiate between supervised and unsupervised learning, and identify appropriate algorithms for various data mining tasks.
• Gain proficiency in using SQL Developer and Oracle Data Miner 4.1 for managing data mining projects.
• Develop skills to create, evaluate, and deploy classification models to predict outcomes based on historical data.
• Acquire the ability to construct and assess regression models for forecasting numerical values.
• Understand clustering models to identify natural groupings within data and interpret the results for strategic insights.
• Perform Market Basket Analysis to analyze transactional data and generate association rules for decision support.
• Learn to detect anomalies in datasets using appropriate models and algorithms, assessing the results for further action.
• Explore methods to mine both structured and unstructured data, including text mining and handling nested data.
• Discover how to construct predictive queries to anticipate future trends or behaviors directly within Oracle Database.
• Learn deployment strategies for predictive models, including requirements and options for operational use.