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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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      Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions (Q48-Q53):

      NEW QUESTION # 48
      Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

      Answer: B

      Explanation:
      The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI ' s OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.


      NEW QUESTION # 49
      Which AI Ethics principle leads to the Responsible AI requirement of transparency?

      Answer: D


      NEW QUESTION # 50
      Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

      Answer: B

      Explanation:
      The OCI Generative AI service offers various categories of pretrained foundational models, including Embedding models, Chat models, and Generation models. These models are designed to perform a wide range of tasks, such as generating text, answering questions, and providing contextual embeddings. However, Translation models, which are typically used for converting text from one language to another, are not a category available in the OCI Generative AI service ' s current offerings. The focus of the OCI Generative AI service is more aligned with tasks related to text generation, chat interactions, and embedding generation rather than direct language translation.


      NEW QUESTION # 51
      What is the primary purpose of reinforcement learning?

      Answer: A

      Explanation:
      Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by taking actions in an environment to achieve a certain goal. The agent receives feedback in the form of rewards or penalties based on the outcomes of its actions, which it uses to learn and improve its decision-making over time. The primary purpose of reinforcement learning is to enable the agent to learn optimal strategies by interacting with its environment, thereby maximizing cumulative rewards. This approach is commonly used in areas such as robotics, game playing, and autonomous systems.


      NEW QUESTION # 52
      What key objective does machine learning strive to achieve?

      Answer: B

      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 # 53
      ......

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