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Oracle 1z0-1122-26 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Intro to OCI AI Services | 20% | - OCI Vision - OCI Language - OCI Document Understanding - OCI Speech |
| Topic 2: Intro to ML Foundations | 15% | - Discuss Supervised Learning Fundamentals
- Discuss Unsupervised Learning Fundamentals - Discuss Reinforcement Learning Fundamentals |
| Topic 3: Intro to DL Foundations | 15% | - Discuss Deep Learning Fundamentals - Explain Sequence Models (RNN and LSTM) - Explain Convolutional Models (CNN) |
| Topic 4: Get started with OCI AI Portfolio | 15% | - Discuss OCI AI Infrastructure Overview - Explain Responsible AI - Discuss OCI AI Services Overview - Discuss OCI ML Services Overview |
| Topic 5: Intro to Generative AI and LLMs | 15% | - Explain Transformers Fundamentals - Discuss Large Language Models Fundamentals - Explain LLM Fine Tuning - Explain Prompt Engineering and Instruction Tuning - Discuss Generative AI Overview |
| Topic 6: OCI Generative AI and Oracle 23ai | 10% | - Discuss Oracle Vector Search - Describe OCI Generative AI Services - Discuss Autonomous Database Select AI |
| Topic 7: Intro to AI Foundations | 10% | - Explain AI vs ML vs DL - Discuss AI Basics - Discuss AI Applications and Types of Data |
Oracle Cloud Infrastructure 2026 AI Foundations Associate Sample Questions:
Question 1
How does AI enhance human efforts?
A. By increasing the physical strength of humans
B. By deleting data humans need to handle
C. By completely replacing human workers in all tasks
D. By processing data at a speed and effectiveness far beyond human capability
Question 2
A customer feedback analysis team needs to extract insights from thousands of online product reviews. They want to determine whether customers express positive or negative opinions about different aspects of a product or service. Which feature of OCI Language is helpful?
A. Key phrase extraction
B. Language detection
C. Sentiment analysis
D. Named entity recognition
Question 3
How do Large Language Models (LLMs) handle the trade-off between model size, data quality, data size and performance?
A. They disregard model size and prioritize high-quality data only.
B. They ensure that the model size, training time, and data size are balanced for optimal results.
C. They focus on increasing the number of tokens while keeping the model size constant.
D. They prioritize larger model sizes to achieve better performance.
Question 4
What is the key feature of Recurrent Neural Networks (RNNs)?
A. They are primarily used for image recognition tasks.
B. They do not have an internal state.
C. They process data in parallel.
D. They have a feedback loop that allows information to persist across different time steps.
Question 5
Which AI Ethics principle leads to the Responsible AI requirement of transparency?
A. Prevention of harm
B. Explicability
C. Respect for human autonomy
D. Fairness
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: B | Question 4 Answer: D | Question 5 Answer: B |
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