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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
  • 1. Generative AI capabilities on OCI
    • 2. Oracle 23ai Vector Database integration
      Topic 2: 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
          Topic 3: Deep Learning Foundations15%- Deep Learning and neural networks
          • 1. Convolutional Neural Networks (CNN) architectures
            • 2. Recurrent Neural Networks, LSTMs, and sequence models
              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: Machine Learning Foundations15%- Machine Learning fundamentals
                  • 1. Unsupervised learning: clustering and dimensionality reduction
                    • 2. Reinforcement learning basics and model evaluation concepts
                      • 3. Supervised learning: regression and classification
                        Topic 6: Introduction to OCI AI Services20%- OCI AI Service APIs
                        • 1. OCI Language, Vision, Speech, and Document Understanding services
                          • 2. OCI Select AI and AI service use cases
                            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 (Q37-Q42):

                                NEW QUESTION # 37
                                Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?

                                Answer: A

                                Explanation:
                                Artificial Intelligence (AI) is the broadest field encompassing all technologies that enable machines to perform tasks that typically require human intelligence. Within AI, Machine Learning (ML) is a subset focused on the development of algorithms that allow systems to learn from and make predictions or decisions based on data. Deep Learning (DL) is a further subset of ML, characterized by the use of artificial neural networks with many layers (hence " deep " ).
                                In this hierarchy:
                                * AI includes all methods to make machines intelligent.
                                * ML refers to the methods within AI that focus on learning from data.
                                * DL is a specialized field within ML that deals with deep neural networks.


                                NEW QUESTION # 38
                                Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

                                Answer: D

                                Explanation:
                                The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI ' s OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.


                                NEW QUESTION # 39
                                What is the primary purpose of reinforcement learning?

                                Answer: B

                                Explanation:
                                Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by taking actions in an environment to achieve a certain goal. The agent receives feedback in the form of rewards or penalties based on the outcomes of its actions, which it uses to learn and improve its decision-making over time. The primary purpose of reinforcement learning is to enable the agent to learn optimal strategies by interacting with its environment, thereby maximizing cumulative rewards. This approach is commonly used in areas such as robotics, game playing, and autonomous systems.


                                NEW QUESTION # 40
                                Which AI Ethics principle leads to the Responsible AI requirement of transparency?

                                Answer: B


                                NEW QUESTION # 41
                                What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

                                Answer: D


                                NEW QUESTION # 42
                                ......

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