CPMAI_v7 Free Practice Test

You're working with an inexperienced team and this is all their first AI project. You're trying to work on a supervised learning binary classification problem to determine if emails are spam or not.
What is the best approach for this project?

1. A. Pick a simple algorithm such as naive bayes
2. B. Pick a neural network algorithm since you know this works well for supervised learning approaches
3. C. Pick an ensemble method since you're not sure which algorithm will perform best
4. D. Pick a simple algorithm such as Gaussian mixture

Correct Answer: A
Naive Bayes classifiers are a family of "simple probabilistic classifiers based on Bayes' theorem with the 'naive' assumption of feature independence," making them fast to train and easy to interpret - ideal for teams new to AI tackling binary tasks like spam detection .

- [AI Fundamentals]
Use cognitive technologies/AI when you can't code the rules or you can't scale easily with people or automation. As a good rule of thumb when deciding if AI is right for the project you should:

1. A. Decide if it's a statistics patter
2. B. If it's statistical then go with the AI project.
3. C. Decide if it's probabilistic or deterministic pattern
4. D. If it's deterministic then go with the AI project.
5. E. See if simple rules wor
6. F. If yes, then pick the right AI solution to solve the problem.
7. G. Decide if it's probabilistic or deterministic pattern
8. H. If it's probabilistic then go with the AI project.

Correct Answer: D
The CPMAI™ Glossary contrasts automation (for deterministic, rule-based tasks) with AI (for probabilistic, learning-based tasks). As a rule of thumb, if a problem exhibits probabilistic patterns that can't be captured by fixed rules, then AI is the appropriate solution; deterministic problems are better handled by simple automation.

- [Data for AI]
Enhancing and cleaning data is an important action during which phase of CPMAI?

1. A. Phase VI
2. B. Phase I
3. C. Phase V
4. D. Phase III
5. E. Phase II
6. F. Phase IV

Correct Answer: D
The CPMAI™ v7 methodology groups all data-centric preparation activities—including both data cleansing (??Clean data??) and data augmentation (??Enhance & Augment data??)—into Phase III: Data Preparation. In this phase, teams focus squarely on constructing the dataset to be used for modeling by performing all required cleaning, transformation, and enhancement operations.
Phase III: Data Preparation is defined in the Workbook??s Table of Contents as covering Data Cleansing & Enhancement tasks (??Clean data?? and ??Enhance & Augment data??) .
Under Phase III, the Generic Task Group: Data Cleansing & Enhancement explicitly lists ??Task: Clean data?? (bringing data quality to modeling-ready levels) and ??Task: Enhance & Augment data?? (producing derived attributes and new records) as core activities .

- [Trustworthy AI]
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?

1. A. Transparent AI
2. B. Governed AI
3. C. Responsible AI
4. D. Explainable AI

Correct Answer: C
Under Domain VI: Trustworthy AI in the CPMAI Exam Content Outline, Responsible AI covers establishing policies, guidelines, and governance that ensure AI solutions are developed for positive, ethical use and prevent misuse. Defining proper-use guidelines and embedding ethical intent into facial recognition directly align with Responsible AI practices .

- [AI Fundamentals]
Which of the following best describes the technical definition of Machine Learning?

1. A. An approach to using increasing levels of intelligence to solve greater cognitive needs from unintelligent automation to autonomous business process.
2. 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.
3. C. The application of pre-defined rules and algorithms to solve complex problems.
4. D. The use of computing technology to enable machines to gain cognitive intelligence.

Correct Answer: B
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.??) .