Oracle 1Z0-1110-26 Prüfungsthemen:
| Abschnitt | Gewichtung | Ziele |
|---|---|---|
| Thema 1: OCI Data Science - Einführung & Konfiguration | 10% | - Tenancy- und Umgebungskonfiguration für Data Science - Funktionen des Accelerated Data Science (ADS) SDK - Übersicht und Kernkonzepte von OCI Data Science |
| Thema 2: Anwendung von MLOps-Praktiken | 20% | - Governance, Auditierung und Compliance - Modellüberwachung, Drift-Erkennung und Performance-Tracking - ML-Pipelines, Automatisierung und Reproduzierbarkeit |
| Thema 3: Integration verwandter OCI-Services | 10% | - Nutzung von OCI AI- und Datendiensten mit Data Science - Integration mit OCI Object Storage, Vault und Networking |
| Thema 4: Design und Einrichtung des Data Science-Arbeitsbereichs | 15% | - Verwalten von Zugriffskontrolle, Sicherheit und IAM-Integration - Erstellen und Verwalten von Projekten und Notebook-Sessions - Konfigurieren von Compute Shapes, Speicher und Netzwerken |
| Thema 5: Implementierung des End-to-End Machine Learning-Lebenszyklus | 45% | - Modellentwicklung, -training und -evaluierung - Datenvorbereitung, -exploration und -transformation - Modellspeicherung, -katalogisierung und -versionierung - Nutzung von AutoML und integrierten Algorithmen - Bereitstellen von Modellen und Verwalten von Endpunkten |
Oracle Cloud Infrastructure Data Science Professional 1Z0-1110-26 Prüfungsfragen mit Lösungen
Frage #1
You have configured the Management Agent on an Oracle Cloud Infrastructure (OCI) Linux instance for log ingestion purposes. Which is a required configuration for OCI Logging Analytics service to collect data from multiple logs of this instance?
A. Log - Log Group Association
B. Entity - Log Association
C. Log Group - Source Association
D. Source - Entity Association
Frage #2
You want to use ADSTuner to tune the hyperparameters of a supported model you recently trained. You have just started your search and want to reduce the computational cost as well as assess the quality of the model class that you are using. What is the most appropriate search space strategy to choose?
A. Detailed
B. Pass a dictionary that defines a search space
C. Perfunctory
D. ADSTuner doesn’t need a search space to tune the hyperparameters
Frage #3
Which THREE types of data are used for Data Labeling?
A. Images
B. Text Document
C. Graphs
D. Audio
Frage #4
As a data scientist, you create models for cancer prediction based on mammographic images. The correct identification is very crucial in this case. After evaluating two models, you arrive at the following confusion matrix. Which model would you prefer and why?
Model 1 has Test accuracy is 80% and recall is 70%
Model 2 has Test accuracy is 75% and recall is 85%
A. Model 2, because recall has more impact on predictions in this use case
B. Model 1, because recall has lesser impact on predictions in this use case
C. Model 2, because recall is high
D. Model 1, because the test accuracy is high
Frage #5
Which of these options allow the sharing and loading back of ML models into a notebook session?
A. Model catalog
B. Model taxonomy
C. Model provenance
D. Model deployment
Fragen und Antworten:
| Frage #1 Antwort: D | Frage #2 Antwort: C | Frage #3 Antwort: A,B | Frage #4 Antwort: A | Frage #5 Antwort: A |
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