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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: OCI AI Portfolio15%- Overview of OCI AI offerings
  • 1. OCI Data Science and GPU-based compute infrastructure
    • 2. AI Services, ML Services, and AI Infrastructure overview
      Topic 2: OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
      • 1. Generative AI capabilities on OCI
        • 2. Oracle 23ai Vector Database integration
          Topic 3: Generative AI and Large Language Models15%- Generative AI concepts
          • 1. Embeddings, Retrieval-Augmented Generation (RAG), and LLMs
            • 2. Transformers, prompt engineering, and fine-tuning
              Topic 4: Machine Learning Foundations15%- Machine Learning fundamentals
              • 1. Supervised learning: regression and classification
                • 2. Reinforcement learning basics and model evaluation concepts
                  • 3. Unsupervised learning: clustering and dimensionality reduction
                    Topic 5: Deep Learning Foundations15%- Deep Learning and neural networks
                    • 1. Convolutional Neural Networks (CNN) architectures
                      • 2. Recurrent Neural Networks, LSTMs, and sequence models
                        Topic 6: Introduction to OCI AI Services20%- OCI AI Service APIs
                        • 1. OCI Select AI and AI service use cases
                          • 2. OCI Language, Vision, Speech, and Document Understanding services
                            Topic 7: AI Foundations10%- Artificial Intelligence basics and terminology
                            • 1. AI, Machine Learning, and Deep Learning relationship
                              • 2. AI applications, use cases, and responsible AI principles

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                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q29-Q34):

                                NEW QUESTION # 29
                                Which capability is supported by the Oracle Cloud Infrastructure Vision service?

                                Answer: D

                                Explanation:
                                The Oracle Cloud Infrastructure (OCI) Vision service is designed for image analysis tasks, which includes the capability to detect and recognize objects, such as vehicle number plates. This functionality is particularly useful for applications such as automated enforcement of traffic laws, where the system can identify vehicles exceeding speed limits and issue citations based on the detected number plates. This capability leverages advanced computer vision techniques to process and analyze visual data, making it suitable for applications in public safety, transportation, and law enforcement.


                                NEW QUESTION # 30
                                What is the benefit of using embedding models in OCI Generative AI service?

                                Answer: C

                                Explanation:
                                Embedding models in the OCI Generative AI service are designed to represent text, phrases, or other data types in a dense vector space, where semantically similar items are located closer to each other. This representation enables more effective semantic searches, where the goal is to retrieve information based on the meaning and context of the query, rather than just exact keyword matches.
                                The benefit of using embedding models is that they allow for more nuanced and contextually relevant searches. For example, if a user searches for " financial reports, " an embedding model can understand that " quarterly earnings " is semantically related, even if the exact phrase does not appear in the document. This capability greatly enhances the accuracy and relevance of search results, making it a powerful tool for handling large and diverse datasets .


                                NEW QUESTION # 31
                                What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

                                Answer: A


                                NEW QUESTION # 32
                                Lisa is working on a project that involves transcribing thousands of audio files stored in Oracle Cloud. She wants to process multiple files efficiently instead of transcribing them one by one. Which OCI Speech feature should Lisa use?

                                Answer: D

                                Explanation:
                                OCI Speech supports batch transcription for efficiently processing prerecorded media. Lisa ' s key requirement is to process thousands of audio files without manually handling them individually. Oracle documentation explicitly identifies OCI Speech as supporting both real-time and batch transcription, while the OCI Speech documentation includes transcription jobs and large batch jobs among its supported workflows.
                                Oracle Docs Batch support therefore directly addresses high-volume processing of stored audio. Confidence scoring measures the service ' s certainty about recognized speech, timestamping associates transcript content with positions in the source recording, and profanity filtering controls how offensive language is represented.
                                Those capabilities enhance transcription output but do not provide the required multi-file processing mechanism. Consequently, Batch support is the appropriate OCI Speech capability for scalable transcription of Lisa ' s collection of audio files.


                                NEW QUESTION # 33
                                Which AI Ethics principle leads to the Responsible AI requirement of transparency?

                                Answer: D


                                NEW QUESTION # 34
                                ......

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