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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: MLOps and OCI Integration | 20% | - Automation and pipelines
|
| Topic 2: Model Development and Deployment | 30% | - Model deployment
|
| Topic 3: Machine Learning Fundamentals | 20% | - Unsupervised learning
|
| Topic 4: OCI Data Science Service | 30% | - Model catalog
|
世界500強企業中，有超過2/3的企業選擇了 Oracle 電子商務軟體產品作為其核心的運用。因此，獲得 Oracle 的認證，即使在強手林立的競爭環境中，你同樣能夠脫穎而出。考生想要通過 1Z0-1110-26 考試，最快速的方式是使用 Oracle 的 1Z0-1110-26 考題，很多考生都是通過這種方式成功通過考試，可以快速掌握考試的相關資訊。
問題 #70
What is a conda environment?
答案：C
解題說明：
Detailed Answer in Step-by-Step Solution:
Define Conda: Conda is a widely used tool for managing packages and environments in data science.
Evaluate Options:
A: Partially true—Conda manages dependencies, but it’s broader (an environment system).
B: Incorrect—Kernels (e.g., Jupyter) are separate; Conda manages environments.
C: Correct—Conda is an open-source tool for creating isolated environments with specific packages.
D: Incorrect—Not specific to Oracle AI; it’s a general tool.
Reasoning: C captures Conda’s full scope as an open-source system, beyond just dependency management (A).
Conclusion: C is the most accurate.
OCI documentation describes Conda as “an open-source package and environment management system that allows data scientists to create isolated environments with specific versions of Python and libraries.” A is too narrow, B misaligns with kernel concepts, and D ties it incorrectly to Oracle AI. C aligns with Conda’s official definition and OCI’s usage.
1: Oracle Cloud Infrastructure Data Science Documentation, "Conda Environments Overview".
問題 #71
Why is data sampling useful for data scientists?
答案：A
解題說明：
Detailed Answer in Step-by-Step Solution:
Objective: Determine the primary benefit of data sampling.
Define Sampling: Selecting a subset of data to represent the whole—used in ML/statistics.
Evaluate Options:
A: Small batches reduce resources—True but not the main purpose.
B: Reduces storage—Incidental, not the goal.
C: Representative subset for faster, accurate models—Core purpose of sampling.
Reasoning: Sampling speeds up analysis while maintaining accuracy (e.g., training on 10% of data).
Conclusion: C is correct.
OCI documentation states: “Data sampling allows data scientists to use a representative subset of a large dataset to build accurate models more quickly, especially when processing full datasets is impractical.” A focuses on resources (secondary), B on storage (not primary)—only C captures the analytical intent per OCI’s AutoML sampling approach.
1: Oracle Cloud Infrastructure Data Science Documentation, "Data Sampling Techniques".
問題 #72
Which is NOT a part of Observability and Management Services?
答案：B
解題說明：
Detailed Answer in Step-by-Step Solution:
Objective: Identify the non-Observability and Management (O&M) service in OCI.
Understand O&M: Includes monitoring, logging, events tools.
Evaluate Options:
A: Event Services—Triggers actions, part of O&M—correct.
B: OCI Management Service—Not a defined O&M service—incorrect.
C: Logging Analytics—Log analysis, O&M component—correct.
D: Logging—Log collection, O&M component—correct.
Reasoning: B isn’t listed in OCI’s O&M suite—others are.
Conclusion: B is correct (not part of O&M).
OCI documentation lists “Observability and Management Services as including Event Services (A), Logging Analytics (C), and Logging (D)—‘OCI Management Service’ (B) is not a recognized component.” B appears to be a misnomer—only A, C, D are O&M per OCI’s service catalog.
1: Oracle Cloud Infrastructure Observability and Management Documentation, "Service Overview".
問題 #73
Which Oracle Accelerated Data Science (ADS) classes can be used for easy access to datasets from reference libraries and index websites such as scikit-learn?
答案：D
解題說明：
Detailed Answer in Step-by-Step Solution:
Objective: Identify ADS class for dataset access (e.g., scikit-learn).
Evaluate Options:
A: DataLabeling—Not an ADS class.
B: DatasetBrowser—Not real.
C: SecretKeeper—Credentials, not data.
D: DatasetFactory—Loads datasets (e.g., open())—correct.
Reasoning: DatasetFactory simplifies library dataset access.
Conclusion: D is correct.
OCI documentation states: “DatasetFactory (D) in ADS SDK accesses datasets from libraries like scikit-learn (e.g., DatasetFactory.open('sklearn.datasets:load_iris')).” A, B, and C don’t exist or apply—only D fits.
1: Oracle Cloud Infrastructure ADS SDK Documentation, "DatasetFactory".
問題 #74
You realize that your model deployment is about to reach its utilization limit. What would you do to avoid the issue before requests start to fail? Which THREE steps would you perform?
答案：C,D,E
解題說明：
Detailed Answer in Step-by-Step Solution:
Objective: Prevent deployment failure due to utilization limits.
Understand Utilization: High load requires capacity or throttling.
Evaluate Options:
A: More instances—Scales horizontally—correct.
B: Delete—Stops service, not a fix—incorrect.
C: Fewer instances—Worsens issue—incorrect.
D: Larger VM—Scales vertically—correct.
E: Reduce bandwidth—Controls load—correct.
Reasoning: A and D increase capacity, E manages demand—effective trio.
Conclusion: A, D, E are correct.
OCI documentation states: “To avoid utilization limits, increase instances (A), use a larger compute shape (D), or reduce load balancer bandwidth (E) to manage request rates.” B stops service, C reduces capacity—only A, D, E align with OCI’s deployment scaling options.
1: Oracle Cloud Infrastructure Data Science Documentation, "Model Deployment Scaling".
問題 #75
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在你的職業生涯中，你正面臨著挑戰嗎？你想提高自己的技能更好地向別人證明你自己嗎？你想得到更多的機會晉升嗎？那麼快報名參加IT認證考試獲得認證資格吧。Oracle的認證考試是IT領域很重要的考試之一，如果獲得Oracle的認證資格，那麼你就可以得到很大的幫助。你可以先從通過1Z0-1110-26認證考試開始，因為這是Oracle的一個非常重要的考試。那麼，想知道怎麼快速地通過考試嗎？Fast2test的考試資料可以幫助你達到自己的目標。
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