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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions:

                                Question 1

                                What is the purpose of the model catalog in OCI Data Science?

                                A. To store, track, share, and manage models
                                B. To create and switch between different environments
                                C. To deploy models as HTTP endpoints
                                D. To provide a preinstalled open source library


                                Question 2

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

                                A. Respect for human autonomy
                                B. Explicability
                                C. Prevention of harm
                                D. Fairness


                                Question 3

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

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


                                Question 4

                                You are training a logistic regression model to classify emails as spam or not spam. The model is currently classifying too many emails as spam. What would you do to adjust the model?

                                A. Decrease the weight of the feature representing the presence of certain keywords.
                                B. Increase the regularization parameter.
                                C. Increase the threshold value for classification.
                                D. Decrease the number of iterations.


                                Question 5

                                What role do Transformers perform in Large Language Models (LLMs)?

                                A. Provide a mechanism to process sequential data in parallel and capture long-range dependencies
                                B. Limit the ability of LLMs to handle large datasets by imposing strict memory constraints
                                C. Manually engineer features in the data before training the model
                                D. Image recognition tasks in LLMs


                                Solutions:

                                Question 1
                                Answer: A
                                Question 2
                                Answer: B
                                Question 3
                                Answer: D
                                Question 4
                                Answer: C
                                Question 5
                                Answer: A

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