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Oracle Cloud Infrastructure 2026 AI Foundations Associate : 1z0-1122-26 Exam

1z0-1122-26 Exam Questions
  • Exam Code: 1z0-1122-26
  • Exam Name: Oracle Cloud Infrastructure 2026 AI Foundations Associate
  • Updated: Sep 09, 2026
  • Q & A: 49 Questions and Answers
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Oracle 1z0-1122-26 exam demo

Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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 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: 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
                Topic 4: Deep Learning Foundations15%- Deep Learning and neural networks
                • 1. Recurrent Neural Networks, LSTMs, and sequence models
                  • 2. Convolutional Neural Networks (CNN) architectures
                    Topic 5: 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 6: OCI Generative AI and Oracle 23ai10%- OCI Generative AI Service features
                        • 1. Oracle 23ai Vector Database integration
                          • 2. Generative AI capabilities on OCI
                            Topic 7: Generative AI and Large Language Models15%- Generative AI concepts
                            • 1. Transformers, prompt engineering, and fine-tuning
                              • 2. Embeddings, Retrieval-Augmented Generation (RAG), and LLMs

                                Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions:

                                Question #1

                                What is the benefit of using embedding models in OCI Generative AI service?

                                • A. They facilitate semantic searches.
                                • B. They simplify managing databases.
                                • C. They enable creating detailed graphics.
                                • D. They optimize the use of computational resources.
                                Answer: A

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

                                Question #2

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

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

                                Question #3

                                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 detect specific features in the input image.
                                • D. To reduce the spatial dimensions of the input image.
                                Answer: C

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

                                Question #4

                                What is " in-context learning " in the realm of Large Language Models (LLMs)?

                                • A. Teaching a model through zero-shot learning
                                • B. Training a model on a diverse range of tasks
                                • C. Providing a few examples of a target task via the input prompt
                                • D. Modifying the behavior of a pretrained LLM permanently
                                Answer: C

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

                                Question #5

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

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

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