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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 course prerequisites for Oracle Machine Learning using Python training. However, having a foundational understanding of the following concepts will help you get the most out of the training:
1. Basic knowledge of Python programming: Familiarity with Python's data types, variables, control structures, functions, and libraries is essential for working with Oracle Machine Learning.
2. Understanding of machine learning concepts: Knowledge of basic machine learning algorithms, their working, and evaluation metrics will enable you to understand Oracle Machine Learning's features and capabilities.
3. Familiarity with data manipulation and analysis: Having a basic understanding of data manipulation, such as working with pandas and numpy, and data visualization using libraries like Matplotlib and Seaborn will help with data analysis and interpretation using Oracle Machine Learning.
4. Experience with SQL and relational databases: It is helpful to have experience working with SQL queries, especially in Oracle databases, as most Oracle Machine Learning algorithms are implemented using SQL.
5. Knowledge of Oracle Autonomous Database: Familiarity with Oracle Autonomous Database and its features will help you leverage the capabilities of Oracle Machine Learning.
If you're not familiar with these concepts, consider taking introductory courses in Python programming, machine learning, data manipulation, and SQL. Courses or resources on Oracle Machine Learning itself and Oracle Autonomous Database will also be beneficial.
Oracle Machine Learning using Python certification training is a comprehensive program designed to equip learners with the skills required to effectively leverage Python's machine learning capabilities within the Oracle ecosystem. Topics covered in the course include data exploration, data preparation, feature selection, model creation, evaluation, tuning, and deployment. The program focuses on the Oracle Python library (OML4Py) and its integration with various database tools, enabling students to apply cutting-edge machine learning techniques in a familiar environment, enhancing their professional competencies and readiness for the data-driven industry.
Oracle Machine Learning using Python enhances data analytics and predictive modeling capabilities by integrating Python with Oracle Database. Learning this course in stats benefits professionals to efficiently leverage in-database algorithms, advanced analytics, and scalability, providing faster, efficient, and secure access to data, thereby unlocking valuable insights and driving data-driven decision-making.
