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PMI CPMAI Exam Syllabus Topics:

Section	Weight	Objectives
Manage AI Model Development and Evaluation	16%	- Monitor performance, accuracy, and reliability - Address model drift, explainability, and limitations - Oversee model design, training, and validation
Operationalize AI Solution	17%	- Deploy AI systems into production - Establish monitoring, maintenance, and improvement processes - Manage change, adoption, and governance post-launch
Identify Business Needs and Solutions	26%	- Align AI initiatives with organizational strategy - Define requirements, scope, and success criteria - Evaluate feasibility and value of AI solutions
Support Responsible and Trustworthy AI Efforts	15%	- Ensure fairness, transparency, accountability - Establish ethical and governance frameworks - Manage bias, risk, compliance, and societal impact
Identify Data Needs	26%	- Define data requirements and sources - Ensure data quality, privacy, security, and compliance - Plan data collection, storage, and infrastructure

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PMI Cognitive Project Management in AI (PMI-CPMAI) CPMAI Prüfungsfragen mit Lösungen (Q35-Q40):

35. Frage
Using machine learning and other cognitive approaches to understand how to take past/existing behavior and predict future outcomes or help humans make decisions about future outcomes using insight learned from past behavior/interactions/data is a core part to which pattern(s) of AI?

A. Goal Driven Systems
B. Predictive Analytics & Decision Support
C. Predictive Analytics & Decision Support and Patterns and Anomalies
D. Recognition Pattern

Antwort: B

36. Frage
You are leading a project to develop a new predictive maintenance solution. Together with your project team you determine your data needs, see if you have access to the data, and then begin working on the project. Which phase best describes the work you are performing?

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

Antwort: E

Begründung:
Phase II of CPMAI focuses on understanding and preparing data needs, including data acquisition and assessment before model development begins.

37. Frage
A retail bank wants to reduce fraudulent transactions by detecting unusual card activity in near real time. Which AI capability should be used?

A. Autonomous systems
B. Predictive analytics
C. Hyperpersonalization
D. Conversational

Antwort: B

Begründung:
PMI's Seven Patterns of AI describes Predictive analytics & decision support as using data-driven learning to anticipate outcomes and support decisions under uncertainty. Fraud detection is a classic predictive use case: the system analyzes historical and current transaction behaviors to estimate the probability of fraud and recommend actions (approve, decline, escalate). In CPMAI- aligned delivery, the project manager ensures the AI capability matches the business objective and defines measurable performance metrics and thresholds (e.g., false positives, fraud loss reduction, detection latency). PMI-CPMAI also emphasizes responsible and trustworthy AI practices--particularly around privacy, governance, and monitoring--because fraud models can affect customers' access to funds and may introduce bias if training data is skewed. Predictive analytics best fits because it supports classification/risk scoring decisions; the other options focus on interaction (conversational), tailored experiences (hyperpersonalization), or self-directed control (autonomous systems).

38. Frage
A manufacturing company is using an AI system for quality control. The project manager needs to ensure data privacy and compliance with industry standards. Which initial approach will effectively address these requirements?

A. Establishing a data privacy task force
B. Conducting regular data privacy audits
C. Developing a comprehensive data governance plan
D. Implementing advanced data encryption methods

Antwort: C

Begründung:
Developing a comprehensive data governance plan is the most effective initial approach because it defines how data is collected, stored, accessed, protected, retained, and monitored in alignment with privacy obligations and industry standards.

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

A. An approach to using increasing levels of intelligence to solve greater cognitive needs from unintelligent automation to autonomous business process.
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. The application of pre-defined rules and algorithms to solve complex problems.

Antwort: B

40. Frage
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