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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionObjectives
Oracle AI and Machine Learning Services- Oracle AI Stack
  • 1. AI infrastructure
    • 2. AI data and machine learning services
      - OCI AI Services
      • 1. Speech
        • 2. Vision
          • 3. Language
            • 4. Document Understanding
              - OCI Machine Learning Services
              • 1. Machine learning capabilities in OCI
                • 2. OCI Data Science and machine learning workflows
                  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
                          Artificial Intelligence and Machine Learning Fundamentals- Machine Learning Fundamentals
                          • 1. Machine learning models and architectures
                            • 2. Supervised and unsupervised learning
                              - 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
                                      OCI Generative AI and Oracle Database AI Capabilities- 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
                                              - AI Application Frameworks
                                              • 1. Retrieval and AI application concepts
                                                • 2. Language frameworks

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q47-Q52):

                                                  NEW QUESTION # 47
                                                  What is " in-context learning " in the realm of Large Language Models (LLMs)?

                                                  Answer: D

                                                  Explanation:
                                                  " In-context learning " in the realm of Large Language Models (LLMs) refers to the ability of these models to learn and adapt to a specific task by being provided with a few examples of that task within the input prompt.
                                                  This approach allows the model to understand the desired pattern or structure from the given examples and apply it to generate the correct outputs for new, similar inputs. In-context learning is powerful because it does not require retraining the model; instead, it uses the examples provided within the context of the interaction to guide its behavior.


                                                  NEW QUESTION # 48
                                                  Which AI Ethics principle leads to the Responsible AI requirement of transparency?

                                                  Answer: B


                                                  NEW QUESTION # 49
                                                  You are part of the medical transcription team and need to automate transcription tasks. Which OCI AI service are you most likely to use?

                                                  Answer: C

                                                  Explanation:
                                                  For automating transcription tasks in a medical transcription team, the most appropriate OCI AI service to use would be the " Speech " service. This service is designed to convert spoken language into text, which is essential for transcribing spoken medical reports or consultations into written form. The OCI Speech service provides capabilities such as speech-to-text conversion, which is specifically tailored for handling audio input and producing accurate transcriptions.


                                                  NEW QUESTION # 50
                                                  Which algorithm is primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN)?

                                                  Answer: B

                                                  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 # 51
                                                  Which feature is NOT available as part of OCI Speech capabilities?

                                                  Answer: A

                                                  Explanation:
                                                  OCI Speech capabilities are designed to be user-friendly and do not require extensive data science experience to operate. The service provides features such as transcribing audio and video files into text, offering grammatically accurate transcriptions, supporting multiple languages, and providing timestamped outputs.
                                                  These capabilities are built to be accessible to a broad range of users, making speech-to-text conversion seamless and straightforward without the need for deep technical expertise.


                                                  NEW QUESTION # 52
                                                  ......

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