Pass the actual test with the help of CPMAI study guide
Last Updated: Aug 07, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify Business Needs and Solutions | 26% | - Evaluate feasibility and value of AI solutions - Define requirements, scope, and success criteria - Align AI initiatives with organizational strategy |
| Topic 2: Operationalize AI Solution | 17% | - Establish monitoring, maintenance, and improvement processes - Manage change, adoption, and governance post-launch - Deploy AI systems into production |
| Topic 3: Support Responsible and Trustworthy AI Efforts | 15% | - Manage bias, risk, compliance, and societal impact - Establish ethical and governance frameworks - Ensure fairness, transparency, accountability |
| Topic 4: Identify Data Needs | 26% | - Define data requirements and sources - Ensure data quality, privacy, security, and compliance - Plan data collection, storage, and infrastructure |
| Topic 5: Manage AI Model Development and Evaluation | 16% | - Address model drift, explainability, and limitations - Monitor performance, accuracy, and reliability - Oversee model design, training, and validation |
1. An AI solution performs well in testing but fails after deployment due to differences between training data and real-world production data. The team identifies discrepancies in feature distributions across environments. What is the primary issue affecting performance?
A) Data drift between environments
B) Underfitting
C) Hardware constraints
D) Model bias
2. The team is working to build a data preparation pipeline for the conversational chatbot project.
Which phase of CPMAI is this done?
A) Phase I
B) Phase III
C) Phase VI
D) Phase II
E) Phase V
F) Phase IV
3. Your team is working on a new facial recognition application. Since this technology has the potential to be mis-used you think it's important to set guidelines for the proper use of this application and you want to make sure the AI system is built for some positive purpose. What area of Trustworthy AI does this best fall under?
A) Explainable AI
B) Responsible AI
C) Governed AI
D) Transparent AI
4. A financial services firm is building an AI model to detect fraudulent transactions. Identifying and validating data sources is critical to the model's success. What is an effective method that helps to ensure data accuracy?
A) Setting up a batch processing system for data cleansing
B) Implementing a blockchain-based ledger for transaction data
C) Employing a federated database system for decentralized data access
D) Utilizing data lineage tools to track data origin and transformations
5. Your team is running a forecasting project and wants to use previous user data to better predict future outcomes. However, your team doesn't have access to all the data it needs. What's the best course of action?
A) Move ahead as planned so you stay on time with your project.
B) Do not move forward until you have access to all the data you need.
C) Move ahead as planned and hope you get access to the data once you need it. Since you're using an iterative approach you can always go back to steps as needed later on.
D) Cautiously move forward knowing you may need to pause mid-project which is ok.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: D | Question # 5 Answer: D |
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