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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Deep Learning Foundations15%- Deep Learning and neural networks
  • 1. Convolutional Neural Networks (CNN) architectures
    • 2. Recurrent Neural Networks, LSTMs, and sequence models
      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
          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
                AI Foundations10%- Artificial Intelligence basics and terminology
                • 1. AI applications, use cases, and responsible AI principles
                  • 2. AI, Machine Learning, and Deep Learning relationship
                    Generative AI and Large Language Models15%- Generative AI concepts
                    • 1. Embeddings, Retrieval-Augmented Generation (RAG), and LLMs
                      • 2. Transformers, prompt engineering, and fine-tuning
                        OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
                        • 1. Generative AI capabilities on OCI
                          • 2. Oracle 23ai Vector Database integration
                            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

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                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q10-Q15):

                                NEW QUESTION # 10
                                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 # 11
                                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 # 12
                                You are training a deep learning model to classify images. What is the primary function of the convolutional layer?

                                Answer: C

                                Explanation:
                                A convolutional layer is designed to learn local visual features from an input image. During training, small learnable filters move across the image and respond to patterns such as edges, corners, textures, and progressively more complex structures. The resulting feature maps preserve useful spatial relationships while transforming raw pixels into representations that later layers can use. Oracle documentation recognizes convolutional neural networks as suitable neural-network architectures for visual data and identifies architectures such as ResNet for processing images. Oracle Docs The convolutional layer itself does not primarily generate images or make the final classification decision. Reducing spatial dimensions is normally performed through pooling or strided operations. Therefore, detecting specific features in the input image is the correct function.


                                NEW QUESTION # 13
                                You are working on a project for a healthcare organization that wants to develop a system to predict the severity of patients ' illnesses upon admission to a hospital. The goal is to classify patients into three categories - Low Risk, Moderate Risk, and High Risk - based on their medical history and vital signs. Which type of supervised learning algorithm is required in this scenario?

                                Answer: D

                                Explanation:
                                In this healthcare scenario, where the goal is to classify patients into three categories-Low Risk, Moderate Risk, and High Risk-based on their medical history and vital signs, a Multi-Class Classification algorithm is required. Multi-class classification is a type of supervised learning algorithm used when there are three or more classes or categories to predict. This method is well-suited for situations where each instance needs to be classified into one of several categories, which aligns with the requirement to categorize patients into different risk levels.


                                NEW QUESTION # 14
                                Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

                                Answer: B

                                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 # 15
                                ......

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