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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionObjectives
OCI Generative AI and Oracle Database AI Capabilities- 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
          - AI Application Frameworks
          • 1. Retrieval and AI application concepts
            • 2. Language frameworks
              Generative AI and Large Language Models- Large Language Models
              • 1. LLM fundamentals
                • 2. Language models and generative AI applications
                  - Generative AI Fundamentals
                  • 1. Generative AI concepts and capabilities
                    • 2. Generative AI use cases
                      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
                                      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

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q42-Q47):

                                                  NEW QUESTION # 42
                                                  A customer feedback analysis team needs to extract insights from thousands of online product reviews. They want to determine whether customers express positive or negative opinions about different aspects of a product or service. Which feature of OCI Language is helpful?

                                                  Answer: A

                                                  Explanation:
                                                  OCI Language provides pretrained natural language processing capabilities for analyzing unstructured text, including sentiment analysis. In this scenario, the requirement is specifically to determine whether customers express positive or negative opinions concerning individual aspects of a product or service. Oracle ' s OCI Language customer-feedback architecture describes extracting aspects from reviews and associating sentiments such as positive, negative, or neutral with those aspects. Oracle Docs Key phrase extraction identifies important topics or phrases, named entity recognition identifies entities such as organizations, people, or locations, and language detection determines the language in which content is written. None directly evaluates customer opinion. Sentiment analysis therefore precisely matches the business requirement because it transforms subjective review content into structured sentiment information that can be analyzed at scale.


                                                  NEW QUESTION # 43
                                                  What can Oracle Cloud Infrastructure Document Understanding NOT do?

                                                  Answer: D

                                                  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 # 44
                                                  Emma is developing a customer support chatbot for an e-commerce website. The chatbot needs to provide accurate and up-to-date return policies, which change frequently. She initially tries fine-tuning but finds that the model still uses outdated information. Which approach should Emma use instead?

                                                  Answer: D

                                                  Explanation:
                                                  Retrieval-Augmented Generation is the appropriate approach when a chatbot must answer using information that changes frequently. Oracle defines RAG as a technique that retrieves information from specific external data sources and augments an LLM ' s response with that retrieved context, producing grounded answers.
                                                  Oracle Docs Oracle further explains that RAG can incorporate information that is more current than the model
                                                  ' s original training data and that knowledge repositories can be continually updated without retraining the underlying LLM. Oracle Docs Fine-tuning is better suited to adapting model behavior or specialization, not continuously changing factual information. Prompt engineering and zero-shot prompting control how instructions are presented but do not independently supply current return-policy data. Therefore, RAG is the correct solution for providing accurate, current, organization-specific policy responses.


                                                  NEW QUESTION # 45
                                                  What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

                                                  Answer: C

                                                  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 # 46
                                                  What is the primary benefit of using the OCI Language service for text analysis?

                                                  Answer: D

                                                  Explanation:
                                                  The primary benefit of using the OCI Language service for text analysis is its ability to scale text analysis without requiring users to have extensive machine learning expertise. The service abstracts the complexities of machine learning, allowing businesses to easily process and analyze large amounts of text data through pre- built models. This accessibility makes it possible for a broader range of users to leverage advanced text analysis capabilities, facilitating insights from textual data without needing to develop and train models from scratch.


                                                  NEW QUESTION # 47
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