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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionObjectives
Oracle AI and Machine Learning Services- OCI Machine Learning Services
  • 1. OCI Data Science and machine learning workflows
    • 2. Machine learning capabilities in OCI
      - Oracle AI Stack
      • 1. AI data and machine learning services
        • 2. AI infrastructure
          - OCI AI Services
          • 1. Language
            • 2. Vision
              • 3. Document Understanding
                • 4. Speech
                  Generative AI and Large Language Models- Generative AI Fundamentals
                  • 1. Generative AI use cases
                    • 2. Generative AI concepts and capabilities
                      - Large Language Models
                      • 1. Language models and generative AI applications
                        • 2. LLM fundamentals
                          Artificial Intelligence and Machine Learning Fundamentals- Artificial Intelligence Concepts
                          • 1. AI use cases and applications
                            • 2. AI fundamentals and terminology
                              - Deep Learning Fundamentals
                              • 1. Neural networks
                                • 2. Convolutional and sequence models
                                  - Machine Learning Fundamentals
                                  • 1. Supervised and unsupervised learning
                                    • 2. Machine learning models and architectures
                                      OCI Generative AI and Oracle Database AI Capabilities- AI Application Frameworks
                                      • 1. Language frameworks
                                        • 2. Retrieval and AI application concepts
                                          - OCI Generative AI
                                          • 1. Generative AI models and applications
                                            • 2. OCI Generative AI services
                                              - Oracle AI Database
                                              • 1. AI capabilities in Oracle Database
                                                • 2. Vector database concepts

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q16-Q21):

                                                  NEW QUESTION # 16
                                                  Which is NOT a capability of OCI Vision ' s image analysis?

                                                  Answer: C

                                                  Explanation:
                                                  OCI Vision ' s image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision ' s image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision ' s core image analysis features.
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                                                  NEW QUESTION # 17
                                                  What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

                                                  Answer: D

                                                  Explanation:
                                                  Oracle Cloud Infrastructure Supercluster is designed to deliver exceptional performance and scalability for complex AI tasks. The primary benefit of this infrastructure is its ability to handle demanding AI workloads, offering high-performance computing (HPC) capabilities that are crucial for training large-scale AI models and processing massive datasets. The architecture of the Supercluster ensures low-latency networking, efficient resource allocation, and high-throughput processing, making it ideal for AI tasks that require significant computational power, such as deep learning, data analytics, and large-scale simulations.


                                                  NEW QUESTION # 18
                                                  You are working on a project for a healthcare organization that wants to develop a system to predict the severity of patients ' illnesses upon admission to a hospital. The goal is to classify patients into three categories - Low Risk, Moderate Risk, and High Risk - based on their medical history and vital signs. Which type of supervised learning algorithm is required in this scenario?

                                                  Answer: A

                                                  Explanation:
                                                  In this healthcare scenario, where the goal is to classify patients into three categories-Low Risk, Moderate Risk, and High Risk-based on their medical history and vital signs, a Multi-Class Classification algorithm is required. Multi-class classification is a type of supervised learning algorithm used when there are three or more classes or categories to predict. This method is well-suited for situations where each instance needs to be classified into one of several categories, which aligns with the requirement to categorize patients into different risk levels.


                                                  NEW QUESTION # 19
                                                  What feature of OCI Data Science provides an interactive coding environment for building and training models?

                                                  Answer: D

                                                  Explanation:
                                                  In OCI Data Science, Notebook sessions provide an interactive coding environment that is essential for building, training, and deploying machine learning models. These sessions allow data scientists to write and execute code in real time, offering a flexible environment for data exploration, model experimentation, and iterative development. The integration with various OCI services and support for popular machine learning frameworks further enhances the utility of Notebook sessions, making them a crucial tool in the data science workflow.


                                                  NEW QUESTION # 20
                                                  Which feature is NOT supported as part of the OCI Language service ' s pretrained language processing capabilities?

                                                  Answer: B

                                                  Explanation:
                                                  The OCI Language service offers several pretrained language processing capabilities, including Text Classification, Sentiment Analysis, and Language Detection. However, it does not natively support Text Generation as a part of its core language processing capabilities. Text Generation typically involves creating new content based on input prompts, which is a feature more commonly associated with models specifically designed for natural language generation.


                                                  NEW QUESTION # 21
                                                  ......

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