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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
There are no specific prerequisites mentioned for Machine Learning on Oracle Training. However, to make the most of the training and be able to apply the concepts effectively, it would be helpful to have some background in the following areas:
1. Basic understanding of Oracle Database: Familiarity with the Oracle Database environment, SQL queries, and PL/SQL will help you leverage the platform for machine learning tasks.
2. Knowledge of Machine Learning Fundamentals: Understanding the basic concepts of machine learning, such as supervised and unsupervised learning, feature selection, and model evaluation, will allow you to apply them effectively using Oracle's tools.
3. Programming Experience: Being comfortable with programming languages like Python or R can help you interact with the Oracle Machine Learning platform more effectively, although specific programming expertise is not necessary for the training.
4. Familiarity with Data Science Tools: Experience in using data science libraries and tools like Pandas, NumPy, or Scikit-learn will help you grasp the concepts taught in the Machine Learning on Oracle Training course.
5. Experience with Data Analysis: Basic knowledge of data manipulation, analysis, and visualization techniques will help you prepare and analyze data for machine learning tasks in the Oracle environment.
While these skills are not strictly required, having a background in these areas will help you better understand the concepts covered in the Machine Learning on Oracle Training course and apply them effectively in practice.
The Oracle Machine Learning certification training offers comprehensive knowledge on various machine learning concepts and techniques. The course provides a deep understanding of algorithms, models, and tools within the Oracle Advanced Analytics option. Topics covered include data exploration, data preparation, feature selection, model evaluation, regression, classification, clustering, and reinforcement learning. The training prepares individuals for real-world applications by incorporating hands-on exercises and practical projects, allowing them to make data-driven decisions by leveraging machine learning in Oracle environments.
Machine Learning on Oracle offers a comprehensive understanding of statistical modeling and predictive analysis capabilities. Learning this course equips professionals with valuable skills needed to tackle complex data-driven challenges, optimize business solutions, and stay competitive in today's rapidly evolving digital landscape.
