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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q47-Q52):

                                                  NEW QUESTION # 47
                                                  You are part of the medical transcription team and need to automate transcription tasks. Which OCI AI service are you most likely to use?

                                                  Answer: D

                                                  Explanation:
                                                  For automating transcription tasks in a medical transcription team, the most appropriate OCI AI service to use would be the " Speech " service. This service is designed to convert spoken language into text, which is essential for transcribing spoken medical reports or consultations into written form. The OCI Speech service provides capabilities such as speech-to-text conversion, which is specifically tailored for handling audio input and producing accurate transcriptions.


                                                  NEW QUESTION # 48
                                                  You are training a deep learning model to classify images. What is the primary function of the convolutional layer?

                                                  Answer: D

                                                  Explanation:
                                                  A convolutional layer is designed to learn local visual features from an input image. During training, small learnable filters move across the image and respond to patterns such as edges, corners, textures, and progressively more complex structures. The resulting feature maps preserve useful spatial relationships while transforming raw pixels into representations that later layers can use. Oracle documentation recognizes convolutional neural networks as suitable neural-network architectures for visual data and identifies architectures such as ResNet for processing images. Oracle Docs The convolutional layer itself does not primarily generate images or make the final classification decision. Reducing spatial dimensions is normally performed through pooling or strided operations. Therefore, detecting specific features in the input image is the correct function.


                                                  NEW QUESTION # 49
                                                  What can Oracle Cloud Infrastructure Document Understanding NOT do?

                                                  Answer: B

                                                  Explanation:
                                                  Oracle Cloud Infrastructure (OCI) Document Understanding service offers several capabilities, including extracting tables, classifying documents, and extracting text. However, it does not generate transcripts from documents. Transcription typically refers to converting spoken language into written text, which is a function associated with speech-to-text services, not document understanding services. Therefore, generating a transcript is outside the scope of what OCI Document Understanding is designed to do .


                                                  NEW QUESTION # 50
                                                  Which type of machine learning is used to understand relationships within data and is not focused on making predictions or classifications?

                                                  Answer: C

                                                  Explanation:
                                                  Unsupervised learning is a type of machine learning that focuses on understanding relationships within data without the need for labeled outcomes. Unlike supervised learning, which requires labeled data to train models to make predictions or classifications, unsupervised learning works with unlabeled data and aims to discover hidden patterns, groupings, or structures within the data.
                                                  Common applications of unsupervised learning include clustering, where the algorithm groups data points into clusters based on similarities, and association, where it identifies relationships between variables in the dataset. Since unsupervised learning does not predict outcomes but rather uncovers inherent structures, it is ideal for exploratory data analysis and discovering previously unknown patterns in data .


                                                  NEW QUESTION # 51
                                                  Which AI Ethics principle leads to the Responsible AI requirement of transparency?

                                                  Answer: C

                                                  Explanation:
                                                  Explicability is the AI Ethics principle that leads to the Responsible AI requirement of transparency. This principle emphasizes the importance of making AI systems understandable and interpretable to humans.
                                                  Transparency is a key aspect of explicability, as it ensures that the decision-making processes of AI systems are clear and comprehensible, allowing users to understand how and why a particular decision or output was generated. This is critical for building trust in AI systems and ensuring that they are used responsibly and ethically.
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                                                  NEW QUESTION # 52
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