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We're here to help you find itThe Oracle Database 19c: Data Mining Techniques course is designed to educate learners on the comprehensive features of data mining within the Oracle Database environment. It begins with an Introduction to the fundamental concepts, providing a solid foundation for understanding data mining. The course progresses to Data Mining Concepts and Terminology, clarifying the key terms and principles used in the field.
In The Data Mining Process module, learners are guided through the steps involved in mining data effectively. Oracle Data Miner is introduced, demonstrating how to leverage this tool for mining tasks. The course then delves into practical applications, teaching students about Classification Models, Regression Models, and Clustering Models. Each model is essential for predicting outcomes, trends, and segmenting data.
Advanced techniques like Market Basket Analysis and Anomaly Detection are covered, equipping learners with skills to uncover patterns and outliers. Finally, the course emphasizes the importance of Deploying Data Mining Results, ensuring that the insights gained are effectively integrated into business processes. By completing this course, learners will be able to apply robust data mining techniques using Oracle Database 19c, turning data into actionable intelligence.
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♱ Excluding VAT/GST
Classroom Training price is on request
♱ Excluding VAT/GST
Classroom Training price is on request
Certainly! The Oracle Database 19c: Data Mining Techniques course is designed to provide in-depth knowledge and practical skills on how to use data mining to discover insights, make predictions, and leverage Oracle Database for analytics. To ensure that participants can successfully undertake and benefit from this training, the following prerequisites are recommended:
Basic understanding of database concepts: Familiarity with relational database management systems (RDBMS) and the fundamentals of how databases store and manage data is essential for grasping the concepts taught in the course.
Knowledge of SQL: Participants should have a working knowledge of SQL (Structured Query Language), as it is commonly used for data manipulation and analysis within Oracle Database.
Familiarity with Oracle Database: Having some prior experience with Oracle Database, even at an introductory level, will help participants understand the context and application of data mining techniques within the Oracle environment.
Understanding of basic statistical concepts: A grasp of fundamental statistics, including measures of central tendency, dispersion, and the concept of distributions, will assist in understanding data mining algorithms and interpreting results.
Analytical mindset: An interest in problem-solving and analytical thinking will enable participants to engage with the course material and apply data mining techniques effectively.
These prerequisites are intended to provide a foundation for the course material and help ensure that participants can keep pace with the instruction and fully comprehend the data mining techniques being taught.
The Oracle Database 19c: Data Mining Techniques course equips learners with advanced data analysis skills using Oracle's tools.
Target Audience and Job Roles:
Gain in-depth knowledge of Oracle Database 19c Data Mining techniques, including the process, tools, and models essential for extracting insights from complex data sets.
