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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Foundations10%- Artificial Intelligence basics and terminology
  • 1. AI applications, use cases, and responsible AI principles
    • 2. AI, Machine Learning, and Deep Learning relationship
      Topic 2: 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 3: Deep Learning Foundations15%- Deep Learning and neural networks
          • 1. Recurrent Neural Networks, LSTMs, and sequence models
            • 2. Convolutional Neural Networks (CNN) architectures
              Topic 4: 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 5: 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 6: Machine Learning Foundations15%- Machine Learning fundamentals
                      • 1. Reinforcement learning basics and model evaluation concepts
                        • 2. Unsupervised learning: clustering and dimensionality reduction
                          • 3. Supervised learning: regression and classification
                            Topic 7: OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
                            • 1. Generative AI capabilities on OCI
                              • 2. Oracle 23ai Vector Database integration

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                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q27-Q32):

                                NEW QUESTION # 27
                                What is the primary purpose of reinforcement learning?

                                Answer: C

                                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 # 28
                                What does " fine-tuning " refer to in the context of OCI Generative AI service?

                                Answer: C

                                Explanation:
                                Fine-tuning in the context of the OCI Generative AI service refers to the process of adjusting the parameters of a pretrained model to better fit a specific task or dataset. This process involves further training the model on a smaller, task-specific dataset, allowing the model to refine its understanding and improve its performance on that specific task. Fine-tuning is essential for customizing the general capabilities of a pretrained model to meet the particular needs of a given application, resulting in more accurate and relevant outputs. It is distinct from other processes like encrypting data, upgrading hardware, or simply increasing the complexity of the model architecture.


                                NEW QUESTION # 29
                                Which AI Ethics principle leads to the Responsible AI requirement of transparency?

                                Answer: B


                                NEW QUESTION # 30
                                Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

                                Answer: B

                                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 # 31
                                Which AI Ethics principle leads to the Responsible AI requirement of transparency?

                                Answer: B

                                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 # 32
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