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CPMAI_v7 Simulationsfragen & CPMAI_v7 Unterlage

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>> CPMAI_v7 Simulationsfragen <<

CPMAI_v7 Prüfungsfragen Prüfungsvorbereitungen 2025: Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam - Zertifizierungsprüfung PMI CPMAI_v7 in Deutsch Englisch pdf downloaden

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PMI CPMAI_v7 Prüfungsplan:

Thema
Einzelheiten

Thema 1

Managing AI: This section is for the Project Manager and involves assessing model performance through quality assurance practices, validation techniques, overfitting and underfitting strategies, alignment with KPIs, and iterative refinements. It additionally covers the deployment of AI from training to inference, operationalization in production environments, on-premise or cloud resource selection, data lifecycle management, version control, and the choice of appropriate machine learning services.

Thema 2

Data for AI: This domain targets the Data
AI Lead and explores the central role of data in AI deployments, including Big Data concepts and unstructured data utility. It defines data governance strategies such as steering, stewardship, lifecycle mapping, lineage tracking, and master data practices.

Thema 3

CPMAI Methodology: This domain measures the skills of a Project Manager and outlines the distinctive characteristics of AI projects compared to traditional software development. It investigates failure drivers, ROI justification, data quantity and quality challenges, proof-of-concept issues, real-world deployment barriers, lifecycle continuity, vendor mismatches, stakeholder misalignment, and adaptation of waterfall, lean, and agile approaches through the six phases of the CPMAI framework.

PMI Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam CPMAI_v7 Prüfungsfragen mit Lösungen (Q70-Q75):

70. Frage
Which of the following best describes the technical definition of Machine Learning?

A. The application of pre-defined rules and algorithms to solve complex problems.
B. A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.
C. The use of computing technology to enable machines to gain cognitive intelligence.
D. An approach to using increasing levels of intelligence to solve greater cognitive needs from unintelligent automation to autonomous business process.

Antwort: B

Begründung:
Tom Mitchell's widely adopted formulation captures ML's essence: improvement on task T, measured by P, through experience E. This aligns with CPMAI's view that ML enables systems to learn from data and improve over time ("The ability of a machine to learn from data, improve with experience, and apply that learning to make predictions.") .
=========

71. Frage
You're creating an AI-enabled chatbot that is going to access user data. What areas related to data governance do you need to make sure you're addressing? (Select all that apply.)

A. Change Management Issues
B. Business Risks
C. Data Quantity Issues
D. Security Risks
E. Data Sharing challenges
F. Data Quality Issues
G. Privacy Risks

Antwort: D,E,F,G

Begründung:
Domain IV: Data for AI - Task 2: Implementing Data Governance and Management mandates establishing data stewardship, management plans, lineage, and master-data practices. Core governance concerns include how data is shared (A), ensuring user privacy (B), guarding against breaches (E), and maintaining high data quality (F). Quantity or change-management issues are operational rather than governance controls.
=========

72. Frage
Your team is working on an image recognition system to help identify plants. They have collected a large amount of data but need to get this data labeled.
Which phase of CPMAI is this done?

A. Phase IV
B. Phase VI
C. Phase II
D. Phase III
E. Phase I
F. Phase V

Antwort: D

Begründung:
Phase III: Data Preparation includes the Data Labeling generic task group. Specifically, the Label data task covers "identifying methods for data labeling and engaging in data labeling efforts," which is essential for supervised learning workflows like image recognition.
=========

73. Frage
During CPMAI Phase II of your project, your team is going through their data collection needs. One team member wants to make use of pre-trained models while another member is adamantly against it.
As the project lead, what should you do?

A. Evaluate your data and see if using pre-trained models make sense. If so, have the team see what pre- trained models your company already owns and use those.
B. Have one team build all models in-house and the other team use pre-trained models and see which team' s models perform better.
C. Evaluate your data and use only what you have and build all models in house.
D. Evaluate your data and see if using pre-trained models make sense. If so, have the team do research to find the ones that best suit your project.

Antwort: D

Begründung:
The Pre-Trained and Third-Party Model Usage task in Phase II: Data Understanding directs teams to first assess whether external or foundation models are appropriate given the current data and objectives. If so, they should then research and select the specific pre-trained models that best align with the project's domain, performance needs, and integration constraints. This ensures suitability before committing to fine-tuning or ensemble strategies.
=========

74. Frage
Your team is starting a new facial recognition project and you want to ensure that the project is being done with Trustworthy AI in mind. At what phase of CPMAI would Trustworthy AI be considered?

A. Phase IV
B. Phase VI
C. Phase III
D. Phase II
E. None of the phases
F. All phases
G. Phase I
H. Phase V

Antwort: F

Begründung:
Trustworthy AI is not confined to a single phase but is woven throughout the entire CPMAI lifecycle:
The CPMAI Exam Content Outline under Domain VI: Trustworthy AI specifies tasks such as "Apply ethical AI concepts throughout the development lifecycle," "Ensure compliance with privacy/security requirements," and "Implement transparency and explainability" at every stage .
The CPMAI Workbook's Task Group: Trustworthy AI Requirements (covering transparency, explainability, ethics, compliance, and responsible-AI frameworks) appears as an overarching set of artifacts and considerations that map back to multiple phases-beginning with Business Understanding and continuing through Model Operationalization .
Thus, Trustworthy AI considerations apply across all CPMAI phases.

75. Frage
......

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CPMAI_v7 Unterlage: https://www.deutschpruefung.com/CPMAI_v7-deutsch-pruefungsfragen.html

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Jay Ford Jay Ford

Biography

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