Free PDF Quiz 2026 Oracle 1z0-1122-26 Pass-Sure Latest Dumps

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Oracle 1z0-1122-26 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Get started with OCI AI Portfolio15%- Explain Responsible AI
- Discuss OCI AI Infrastructure Overview
- Discuss OCI ML Services Overview
- Discuss OCI AI Services Overview
Topic 2: Intro to ML Foundations15%- Explain Machine Learning Basics
- Discuss Unsupervised Learning Fundamentals
- Discuss Supervised Learning Fundamentals
  • 1. Regression
    • 2. Classification
      - Discuss Reinforcement Learning Fundamentals
      Topic 3: OCI Generative AI and Oracle 23ai10%- Describe OCI Generative AI Services
      - Discuss Oracle Vector Search
      - Discuss Autonomous Database Select AI
      Topic 4: Intro to OCI AI Services20%- OCI Speech
      - OCI Language
      - OCI Vision
      - OCI Document Understanding
      Topic 5: Intro to DL Foundations15%- Explain Convolutional Models (CNN)
      - Discuss Deep Learning Fundamentals
      - Explain Sequence Models (RNN and LSTM)
      Topic 6: Intro to Generative AI and LLMs15%- Explain LLM Fine Tuning
      - Discuss Large Language Models Fundamentals
      - Discuss Generative AI Overview
      - Explain Transformers Fundamentals
      - Explain Prompt Engineering and Instruction Tuning
      Topic 7: Intro to AI Foundations10%- Discuss AI Applications and Types of Data
      - Explain AI vs ML vs DL
      - Discuss AI Basics

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      Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q31-Q36):

      NEW QUESTION # 31
      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: C

      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 # 32
      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 # 33
      What does " fine-tuning " refer to in the context of OCI Generative AI service?

      Answer: A

      Explanation:
      Fine-tuning in the context of the OCI Generative AI service refers to the process of adjusting the parameters of a pretrained model to better fit a specific task or dataset. This process involves further training the model on a smaller, task-specific dataset, allowing the model to refine its understanding and improve its performance on that specific task. Fine-tuning is essential for customizing the general capabilities of a pretrained model to meet the particular needs of a given application, resulting in more accurate and relevant outputs. It is distinct from other processes like encrypting data, upgrading hardware, or simply increasing the complexity of the model architecture.


      NEW QUESTION # 34
      What is the purpose of the model catalog in OCI Data Science?

      Answer: D

      Explanation:
      The primary purpose of the model catalog in OCI Data Science is to store, track, share, and manage machine learning models. This functionality is essential for maintaining an organized repository where data scientists and developers can collaborate on models, monitor their performance, and manage their lifecycle. The model catalog also facilitates model versioning, ensuring that the most recent and effective models are available for deployment. This capability is crucial in a collaborative environment where multiple stakeholders need access to the latest model versions for testing, evaluation, and deployment.


      NEW QUESTION # 35
      What key objective does machine learning strive to achieve?

      Answer: D

      Explanation:
      The key objective of machine learning is to enable computers to learn from experience and improve their performance on specific tasks over time. This is achieved through the development of algorithms that can learn patterns from data and make decisions or predictions without being explicitly programmed for each task.
      As the model processes more data, it becomes better at understanding the underlying patterns and relationships, leading to more accurate and efficient outcomes.


      NEW QUESTION # 36
      ......

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