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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. Oracle 23ai Vector Database integration
    • 2. Generative AI capabilities on OCI
      Topic 2: 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 3: 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 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. Convolutional Neural Networks (CNN) architectures
                    • 2. Recurrent Neural Networks, LSTMs, and sequence models
                      Topic 6: 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 7: 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

                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions:

                                What feature of OCI Data Science provides an interactive coding environment for building and training models?

                                • A. Accelerated Data Science (ADS) SDK
                                • B. Model catalog
                                • C. Notebook sessions
                                • D. Conda environment
                                Answer: C

                                Explanation: Only visible for iPassleader members. You can sign-up / login (it's free).

                                How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?

                                • A. They disregard model size and prioritize high-quality data only.
                                • B. They focus on increasing the number of tokens while keeping the model size constant.
                                • C. They prioritize larger model sizes to achieve better performance.
                                • D. They ensure that the model size, training time, and data size are balanced for optimal results.
                                Answer: D

                                What is the main function of the hidden layers in an Artificial Neural Network (ANN) when recognizing handwritten digits?

                                • A. Directly predicting the final output
                                • B. Storing the input pixel values
                                • C. Capturing the internal representation of the raw image data
                                • D. Providing labels for the output neurons
                                Answer: C

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                                You are training a deep learning model to classify images. What is the primary function of the convolutional layer?

                                • A. To classify the input image.
                                • B. To generate new images.
                                • C. To reduce the spatial dimensions of the input image.
                                • D. To detect specific features in the input image.
                                Answer: D

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                                How does AI enhance human efforts?

                                • A. By increasing the physical strength of humans
                                • B. By deleting data humans need to handle
                                • C. By processing data at a speed and effectiveness far beyond human capability
                                • D. By completely replacing human workers in all tasks
                                Answer: C

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