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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Machine Learning Foundations15%- Machine Learning fundamentals
  • 1. Unsupervised learning: clustering and dimensionality reduction
    • 2. Supervised learning: regression and classification
      • 3. Reinforcement learning basics and model evaluation concepts
        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: AI Foundations10%- Artificial Intelligence basics and terminology
            • 1. AI, Machine Learning, and Deep Learning relationship
              • 2. AI applications, use cases, and responsible AI principles
                Topic 4: 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 5: Deep Learning Foundations15%- Deep Learning and neural networks
                    • 1. Recurrent Neural Networks, LSTMs, and sequence models
                      • 2. Convolutional Neural Networks (CNN) architectures
                        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: OCI AI Portfolio15%- Overview of OCI AI offerings
                            • 1. AI Services, ML Services, and AI Infrastructure overview
                              • 2. OCI Data Science and GPU-based compute infrastructure

                                >> 1z0-1122-26 Review Guide <<

                                2026 Pass-Sure 1z0-1122-26: Oracle Cloud Infrastructure 2026 AI Foundations Associate Review Guide

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                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q12-Q17):

                                NEW QUESTION # 12
                                Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

                                Answer: D

                                Explanation:
                                Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.


                                NEW QUESTION # 13
                                Which capability is supported by the Oracle Cloud Infrastructure Vision service?

                                Answer: A

                                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 # 14
                                What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

                                Answer: A

                                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 # 15
                                Which feature of OCI Speech helps make transcriptions easier to read and understand?

                                Answer: A

                                Explanation:
                                The text normalization feature of OCI Speech helps make transcriptions easier to read and understand by converting spoken language into a more standardized and grammatically correct format. This process includes correcting grammar, punctuation, and formatting, ensuring that the transcribed text is clear, accurate, and suitable for various use cases. Text normalization enhances the usability of transcriptions, making them more accessible and easier to process in downstream applications.
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                                NEW QUESTION # 16
                                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: B

                                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 # 17
                                ......

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