2026 Efficient Oracle 1z0-1122-26: New Oracle Cloud Infrastructure 2026 AI Foundations Associate Test Practice

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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionObjectives
Topic 1: Artificial Intelligence and Machine Learning Fundamentals- Deep Learning Fundamentals
  • 1. Convolutional and sequence models
    • 2. Neural networks
      - Artificial Intelligence Concepts
      • 1. AI fundamentals and terminology
        • 2. AI use cases and applications
          - Machine Learning Fundamentals
          • 1. Machine learning models and architectures
            • 2. Supervised and unsupervised learning
              Topic 2: OCI Generative AI and Oracle Database AI Capabilities- AI Application Frameworks
              • 1. Retrieval and AI application concepts
                • 2. Language frameworks
                  - Oracle AI Database
                  • 1. Vector database concepts
                    • 2. AI capabilities in Oracle Database
                      - OCI Generative AI
                      • 1. OCI Generative AI services
                        • 2. Generative AI models and applications
                          Topic 3: Generative AI and Large Language Models- Generative AI Fundamentals
                          • 1. Generative AI use cases
                            • 2. Generative AI concepts and capabilities
                              - Large Language Models
                              • 1. Language models and generative AI applications
                                • 2. LLM fundamentals
                                  Topic 4: Oracle AI and Machine Learning Services- OCI AI Services
                                  • 1. Speech
                                    • 2. Document Understanding
                                      • 3. Language
                                        • 4. Vision
                                          - Oracle AI Stack
                                          • 1. AI data and machine learning services
                                            • 2. AI infrastructure
                                              - OCI Machine Learning Services
                                              • 1. Machine learning capabilities in OCI
                                                • 2. OCI Data Science and machine learning workflows

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q11-Q16):

                                                  NEW QUESTION # 11
                                                  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 # 12
                                                  Which algorithm is primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN)?

                                                  Answer: A

                                                  Explanation:
                                                  Backpropagation is the algorithm primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN). It is a supervised learning algorithm that calculates the gradient of the loss function with respect to each weight by applying the chain rule, propagating the error backward from the output layer to the input layer. This process updates the weights to minimize the error, thus improving the model ' s accuracy over time.
                                                  * Gradient Descent is closely related as it is the optimization algorithm used to adjust the weights based on the gradients computed by backpropagation, but backpropagation is the specific method used to calculate these gradients.


                                                  NEW QUESTION # 13
                                                  You are training a deep learning model to classify images. What is the primary function of the convolutional layer?

                                                  Answer: D

                                                  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 # 14
                                                  What distinguishes Generative AI from other types of AI?

                                                  Answer: D

                                                  Explanation:
                                                  Generative AI is distinct from other types of AI in that it focuses on creating new content by learning patterns from existing data. This includes generating text, images, audio, and other types of media. Unlike AI that primarily analyzes data to make decisions or predictions, Generative AI actively creates new and original outputs. This ability to generate diverse content is a hallmark of Generative AI models like GPT-4, which can produce human-like text, create images, and even compose music based on the patterns they have learned from their training data.


                                                  NEW QUESTION # 15
                                                  Which is NOT a capability of OCI Vision ' s image analysis?

                                                  Answer: D

                                                  Explanation:
                                                  OCI Vision ' s image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision ' s image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision ' s core image analysis features.
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                                                  NEW QUESTION # 16
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