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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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      Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q13-Q18):

      NEW QUESTION # 13
      Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?

      Answer: B

      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 # 14
      How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?

      Answer: B


      NEW QUESTION # 15
      What does " fine-tuning " refer to in the context of OCI Generative AI service?

      Answer: B

      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 # 16
      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 # 17
      Which feature is NOT available as part of OCI Speech capabilities?

      Answer: C

      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 # 18
      ......

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