PMI CPMAI Prüfungsthemen:
| Abschnitt | Gewichtung | Ziele |
|---|---|---|
| Vertrauenswürdige KI | 9% | - Datenschutz und Datensicherheit - Ethische Aspekte und Vermeidung von Verzerrungen - Transparenz und Nachvollziehbarkeit von Ergebnissen |
| Steuerung von KI-Projekten | 8% | - Führung von Teams und Ressourcenmanagement in KI-Projekten - Risikomanagement in KI-Vorhaben - Stakeholder-Management |
| Daten für KI-Anwendungen | 13% | - Datenaufbereitung und Vorverarbeitung - Grundlagen von DataOps - Datenstrategie und Datenverwaltung |
| Maschinelles Lernen | 13% | - Algorithmen und Modelle (z. B. NLP, Computer Vision) - Tiefes Lernen und Neuronale Netze - Überwachtes, unüberwachtes und bestärkendes Lernen |
| Grundlagen der KI | 16% | - Konzepte und Fachbegriffe der Künstlichen Intelligenz - Möglichkeiten und Grenzen von KI - Arten von KI und maschinellem Lernen |
| CPMAI-Methodik | 41% | - Phase I: Problemidentifizierung
|
PMI Cognitive Project Management in AI (PMI-CPMAI) CPMAI Prüfungsfragen mit Lösungen
1. A company plans to operationalize an AI solution. The project manager needs to ensure model performance is meeting selected thresholds before release. What is an effective way to confirm these thresholds before this release?
A) Testing against validation datasets
B) Running multiple end-user acceptance tests
C) Conducting a series of penetration tests
D) Implementing an impact evaluation
2. An AI project for a financial technology client is at risk due to potential inaccuracies in data aggregation. What is the first step the project manager should take to mitigate the risk?
A) Create a data visualization.
B) Delete the suspicious data manually.
C) Understand the data characteristics.
D) Evaluate the data freshness and relevance.
3. You have been tasked with creating a model that will recommend products based on what other customers have similarly purchased. Which algorithm is the best choice given this situation?
A) Neural Network
B) K-means
C) K Nearest Neighbor
D) Hyperpersonalization
4. Your company is insisting on running an automation project and applying AI best practices and methodologies to the project. You understand that automating things is just the act of using machines to repeat tasks, and does not require AI to achieve results. You think it is overkill but the project moves forward as planned. What would likely have helped avoid this conflict?
A) Senior management should become involved in the project.
B) Everyone on the team should understand the differences between automation and autonomous systems.
C) Nothing - running automation projects like autonomous projects is the correct thing to do.
D) Applying a hybrid approach of automation and AI best practices would have achieved better results.
5. Your team is tasked with selecting an algorithm for a supervised learning classification project.
Which algorithm might you choose?
A) K-nearest neighbor
B) Gaussian mixture
C) K-means
D) Q learning
Fragen und Antworten:
| 1. Frage Antwort: A | 2. Frage Antwort: C | 3. Frage Antwort: C | 4. Frage Antwort: B | 5. Frage Antwort: A |
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