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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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                                                  Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q21-Q26):

                                                  NEW QUESTION # 21
                                                  Lisa is working on a project that involves transcribing thousands of audio files stored in Oracle Cloud. She wants to process multiple files efficiently instead of transcribing them one by one. Which OCI Speech feature should Lisa use?

                                                  Answer: D

                                                  Explanation:
                                                  OCI Speech supports batch transcription for efficiently processing prerecorded media. Lisa ' s key requirement is to process thousands of audio files without manually handling them individually. Oracle documentation explicitly identifies OCI Speech as supporting both real-time and batch transcription, while the OCI Speech documentation includes transcription jobs and large batch jobs among its supported workflows.
                                                  Oracle Docs Batch support therefore directly addresses high-volume processing of stored audio. Confidence scoring measures the service ' s certainty about recognized speech, timestamping associates transcript content with positions in the source recording, and profanity filtering controls how offensive language is represented.
                                                  Those capabilities enhance transcription output but do not provide the required multi-file processing mechanism. Consequently, Batch support is the appropriate OCI Speech capability for scalable transcription of Lisa ' s collection of audio files.


                                                  NEW QUESTION # 22
                                                  Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

                                                  Answer: A

                                                  Explanation:
                                                  Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.


                                                  NEW QUESTION # 23
                                                  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 # 24
                                                  In machine learning, what does the term " model training " mean?

                                                  Answer: C

                                                  Explanation:
                                                  In machine learning, " model training " refers to the process of teaching a model to make predictions or decisions by learning the relationships between input features and the corresponding output. During training, the model is fed a large dataset where the inputs are paired with known outputs (labels). The model adjusts its internal parameters to minimize the error between its predictions and the actual outputs. Over time, the model learns to generalize from the training data to make accurate predictions on new, unseen data.


                                                  NEW QUESTION # 25
                                                  Which feature is NOT available as part of OCI Speech capabilities?

                                                  Answer: B

                                                  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 # 26
                                                  ......

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