1Z0-1104-22 – OCI Security & 1Z0-1110-22 – OCI Data Science

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Oracle Cloud Infrastructure 2022 Security Professional Exam #: 1Z0-1104-22Topic 1: Security Zones and Security Advisor are features in Oracle Cloud Infrastructure (OCI) that provide security insights and recommendations to help secure your resources. Multi-Factor Authentication (MFA), Identity Federation, and Single Sign-On (SSO) are security measures used to authenticate users and control access to resources. Topic 2: Dynamic Groups, Network Sources, and Tag-Based Access Control are features in OCI that allow for flexible and scalable authorization models, including the ability to grant access to groups of resources based on specific criteria. DRG v2 and Peering can be used to secure the connectivity of virtual networks. Topic 3: Security for Oracle Autonomous Database and DB Systems involves securing the access and communication to the database and its data. Penetration and Vulnerability Testing is a security practice that helps identify potential security threats and vulnerabilities in your environment. Topic 4: Cloud security use cases, challenges, and trends involve securing data and resources in the cloud, while taking into account the unique characteristics of the cloud computing model. Designing a scalable authorization model with users, groups, and policies is an important aspect of cloud security. Topic 5: Auditing and review of OCI Audit Logs is a security practice that helps monitor and track access to resources, detect anomalies, and comply with regulations. Conditional and advanced policies can be used to implement fine-grained security controls. Topic 6: Network Security Groups (NSGs) and Security Lists are features in OCI that allow you to define security rules and control access to network resources. Cloud security business drivers and challenges involve balancing the need for security with the need for agility and innovation in the cloud. Topic 7: Designing and implementing a logging and logging analytics solution is important for monitoring and securing resources in the cloud. Site-to-Site VPN and Fast Connect can be used to secure hybrid network connectivity. Topic 8: OCI Shared Security Responsibility Model defines the responsibilities of both OCI and the customer for securing resources in the cloud. Securing OKE and Oracle Functions involves securing the access and communication to the containerized applications. Topic 9: Data Safe is a feature in OCI that provides security and compliance capabilities for data stored in the cloud. Compartments can be used to isolate resources and control access to them. Topic 10: VCN Flow Logs provide visibility into the network traffic flowing in and out of your virtual network. Web Application Firewall (WAF) is a security service that protects web applications from common attacks and threats. Creating and configuring a WAF involves defining security rules and controls for your web application. Oracle Cloud Infrastructure Data Science 2022 Professional Exam #: 1Z0-1110-22Topic 1: In this topic, you will learn how to create and manage projects and notebook sessions in OCI Data Science. You will also get an overview of the concepts involved in OCI Data Science. Topic 2: This topic will cover the configuration and management of source code in code repositories using Git and how to set up your tenancy for OCI Data Science. Topic 3: This topic focuses on creating and training models using OCI and open-source libraries. You will also learn about the capabilities of the Accelerated Data Science (ADS) SDK. Topic 4: Here, you will learn how to implement the end-to-end machine learning lifecycle and design and set up an OCI Data Science Workspace. Topic 5: In this topic, you will learn how to create and use automated ML capabilities from Oracle Auto ML and configure your tenancy for Data Science. Topic 6: You will learn how to create and manage Spark applications using Data Flow and OCI Data Science, and how to create and manage Conda environments. Topic 7: This topic will cover obtaining global and local model explanations and accessing data from different sources. Topic 8: You will learn how to create and export a dataset using OCI Data Labeling and the general MLOps architecture in OCI. Topic 9: This topic will explain the core OCI Open Data Service concepts and how to create and manage jobs for custom tasks. Topic 10: You will learn how to monitor and log using MLOps practices and how to use OCI AI services for ML solutions. Topic 11: This topic covers managing models using the Model Catalog and how to deploy and invoke a cataloged model. Topic 12: In this topic, you will learn about the ML lifecycle overview, storing credentials via OCI Vault, and scaling with OCI Data Science.