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We're here to help you find itThe Oracle Machine Learning with Autonomous Database course is an educational program designed to equip learners with the skills to leverage Oracle Machine Learning (OML) within the Oracle Autonomous Database environment. Throughout the course, participants will explore various components and features of OML, understand how to create and manage workspaces and projects, and how to execute SQL scripts and commands. They'll gain practical knowledge through hands-on experiences with notebooks for Data analysis, learn to collaborate using templates, and manage OML jobs.
Learners will navigate the intricacies of administering OML, working with Oracle Machine Learning using Autonomous Transaction Processing Cloud, and creating impactful visualizations using Oracle Analytics Cloud. By the end of the course, attendees will be proficient in oracle machine learning using autonomous database and oracle machine learning with autonomous database, empowering them to perform Data analysis, machine learning, and data visualization within the Oracle Cloud ecosystem. This comprehensive course roadmap ensures that participants are well-prepared to harness the power of OML for data-driven decision-making.
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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
To successfully undertake training in the Oracle Machine Learning with Autonomous Database course, students should ideally have the following minimum prerequisites:
Please note that while these prerequisites are aimed at ensuring a smooth learning experience, we encourage students with varying levels of expertise and backgrounds to enroll. Our course is designed to guide learners through the fundamentals before progressing to more advanced topics.
The Oracle Machine Learning with Autonomous Database course is designed for IT professionals looking to specialize in data analytics and machine learning.
This course equips participants with comprehensive skills in leveraging Oracle Machine Learning on the Autonomous Database to analyze data, build models, and create visualizations for actionable insights.
Oracle Machine Learning (OML) is a component of Oracle's Autonomous Database that enhances data analysis by enabling powerful machine learning directly on the database. With OML, you can create, train, and deploy machine learning models using the vast data stored in Oracle Databases without moving the data. This integration simplifies the process of applying machine learning, improves performance, and ensures better security by working within the highly automated and optimized environment of the autonomous database. OML allows data scientists and developers to efficiently scale their machine learning applications and deliver more insightful and predictive analytics.
The Oracle Autonomous Database is a cloud-based technology designed to automate many of the routine tasks required to manage a database, such as tuning, patching, updating, and ensuring security. It uses machine learning to improve its efficiency and performance without human intervention. This system simplifies database management and helps to reduce costs and human error, making it a robust solution for businesses of various sizes. It allows both technical and non-technical users to easily deploy, manage, and analyze data seamlessly, enhancing overall productivity and data security.
SQL scripts and commands are written instructions used to interact with databases to manage and manipulate data. These scripts, comprised of SQL (Structured Query Language) commands, perform tasks like retrieving specific information, updating data, or creating and modifying database structures. Commands like SELECT, INSERT, UPDATE, and DELETE help users to query and modify data inline with their specific requirements from databases. Using SQL ensures efficient data management and retrieval in various software applications and database systems.
OML jobs typically refer to roles focused on "Oracle Machine Learning," which leverages Oracle's Autonomous Database to create and manage machine learning models. In this context, Oracle Machine Learning helps automate data science workflows and enables easy deployment of models directly within the database. Utilizing Oracle's Autonomous Database, the platform enhances efficiency by automating database tuning, security, backups, and updates, allowing data scientists to focus more on extracting insights and less on managing the data infrastructure.
Notebooks for data analysis are interactive web tools used by data scientists to combine executable code, visualizations, and narrative text. These digital notebooks, like Jupyter, allow users to write and execute code in segments, display results, and annotate with comments for better understanding and collaboration. They are convenient for experimenting with data step-by-step, sharing insights, and performing complex data analysis tasks efficiently, fostering a clear, replicable pathway to solving data-driven questions. This environment supports various programming languages and integrates seamlessly with data sources, enhancing productivity and data interaction.
Oracle Machine Learning using Autonomous Transaction Processing Cloud optimizes data analysis by leveraging machine learning directly within the database. This technology allows developers and data scientists to create, train, and deploy machine learning models using SQL, providing a seamless and efficient integration with Oracle's autonomous database systems. The platform automatically manages data processing and storage, significantly simplifying predictive analytics and machine learning tasks. This integration minimizes the need for data movement and enables faster, more accurate decision-making, all while ensuring high security and reduced operational costs.
Oracle Analytics Cloud (OAC) is a comprehensive platform designed to help businesses analyze their data stored in various sources, including databases and applications. It offers tools for data visualization, machine learning, and forecasting, enabling users to generate meaningful insights and make informed decisions. With a focus on ease of use, OAC allows users to quickly create reports, dashboards, and metrics without needing extensive technical skills. The platform's integration with Oracle's Autonomous Database enhances capabilities with automated data management and powerful machine learning, facilitating predictive analytics and greater efficiency in handling complex data operations.
Data analysis involves examining raw data to discover trends, extract insights, and inform decision-making. This process uses various statistical tools and methods to make sense of large volumes of data. Professionals leverage these analyses to solve problems, identify opportunities, and make well-informed data-driven decisions. In today's technology landscape, tools like Oracle Machine Learning with Autonomous Database optimize this process by automating data management and analysis, enhancing accuracy and efficiency.
Machine learning is a branch of artificial intelligence that allows computers to learn from data and make decisions without explicit programming. By analyzing large datasets, machine learning algorithms can detect patterns and improve their predictions over time. Oracle Machine Learning with Autonomous Database enhances this process by automating data management tasks, enabling the algorithms to run more efficiently and with greater accuracy. This integration simplifies the workflow, reduces the possibility of human error, and accelerates the deployment of machine learning models, making sophisticated data analysis accessible to a wider range of users.
Data visualization is the process of converting complex data sets into graphical representations, such as charts or graphs. This makes it easier to see patterns, trends, and outliers in the data. By visually presenting the data, decision-makers can better understand the insights, leading to quicker and more effective decision-making. Effective data visualization helps in simplifying the complex data into clear and actionable insights, which is essential in areas requiring quick analysis and decisions.
The Oracle Machine Learning with Autonomous Database course is designed for IT professionals looking to specialize in data analytics and machine learning.
This course equips participants with comprehensive skills in leveraging Oracle Machine Learning on the Autonomous Database to analyze data, build models, and create visualizations for actionable insights.
