QUESTION 41
You’re working on a computer vision application and realize that you do not have enough real world data for the project. You need additional data created to support your training needs. Specifically, the images you need are of people in different poses. What is the best way to obtain this data?

A. Make use of this data from surveillance footage
B. Make use of this data by having employees pose in the positions required
C. Make use of Synthetic Training Data
D. Make use of data from different departments

Correct Answer: C

QUESTION 42
You are working with a dataset that has a high number of dimensions. You’re running into issues because some dimensions don’t have enough real examples to properly train the systems for predictable results. What’s your best course of action?

A. Keep going as planned and the problem will eventually correct itself
B. Try to improve the quality of your data through more preparation
C. Try to get additional data – at least 5 training examples for each dimension in the representation
D. Try to get additional information from project lead to see how many examples per dimension are needed

Correct Answer: C

QUESTION 43
A project manager meets with a customer for initial discussions about an upcoming project. At the end of the meeting, the customer asks the project manager for a rough estimate of the project duration. Based on her experience with three similar projects, the project manager provides an estimate of 8-10 months. What’s wrong with this timeframe?

A. It fits into a waterfall timeframe, but not an agile project timeframe
B. It’s not accounting for potential project delays
C. It’s not accounting for data preparation timelines
D. It’s underestimating the project timeline by 3 months

Correct Answer: C

QUESTION 44
Your team has been asked to summarize and highlight patterns in historical purchasing data, identifying prior performance metrics and patterns. What type of analytics is most appropriate to apply for this need?

A. Diagnostic Analytics
B. Projective Analytics
C. Descriptive Analytics
D. Predictive Analytics

Correct Answer: C

QUESTION 45
You are working for a large multinational organization and have been assigned to a new project For your new ML project you need to make sure you’re managing data privacy and security as you’re working with sensitive customer data. What critical security issues do you need to make sure you address (Select all that apply.):

A. Securing data at rest
B. Securely storing all data collected for training purposes
C. Securing model data and metadata
D. Compliance with Data Privacy Laws even if they are out of your physical jurisdiction

Correct Answer: ACD

QUESTION 46
Your team is looking to develop an RPA bot to help assist call center agents while on providing support. What type of bot should your team be creating?

A. Attended bot
B. Augmented Intelligence
C. RPA is not the right solution to this problem
D. Unattended bot

Correct Answer: A

QUESTION 47
You’re looking to take an image and have a Generative Al solution generate additional content beyond the bounds of the current image size. What Generative Al approach can you use?

A. Use of Generative Outpainting
B. Use of super-resolution to enhance the existing image
C. Prompt engineering for new image generation
D. Use of inpainting to replace image components

Correct Answer: A

QUESTION 48

In order for Supervised Learning approaches to work, they must be fed clean, well-labeled data that the system can use to learn from examples. But how do you get Labeled Data? As a team leader at a small startup, what approach would not be beneficial when trying to gather labeled data?

A. Find a source of already labeled data
B. Get your Users to Do it
C. Contract with Third Party Data Labeling Firms
D. Hire a Contractor Workforce

Correct Answer: B

QUESTION 49
An inexperienced team is training a neural network model on a desktop computer and this is taking a significant amount of time. What would you recommend to them to speed up model training?

A. Use a contractor to do the training portion
B. Train the model over multiple desktop computers
C. Train the model on GPUs
D. Break the dataset up into multiple smaller datasets and train the model on each of the smaller datasets over a desktop computer

Correct Answer: C

QUESTION 50
Creating machine learning models can be complicated. Your team wants to use tools called Automated Machine Learning (AutoML) to simplify the process. You know of another team that has used AutoML tools and it’s saved the team a lot of time. However, what’s the one area you should not have the AutoML tool help with?

A. Automatic model assessment
B. Automatic algorithm selection
C. Iterative modeling and evaluation
D. Automatic hyperparameter tuning
E. Automatic model selection

Correct Answer: A

QUESTION 51
A project manager is leading a complex project for a global financial institution. The project is developing an Al-driven system for real-time fraud detection and risk management. The system needs to adhere to all financial regulations. The project manager has identified skills gaps with the existing available resources. What should the project manager do?

A. Delay the project until internal expertise is developed.
B. Engage consultants to fill the expertise gap.
C. Allocate additional budget for consultant Al training.
D. Proceed with the project until external expertise is needed.

Correct Answer: B

QUESTION 52
A healthcare provider is operationalizing an Al tool to assist in diagnostic processes. To ensure robust model governance, they need to address data privacy and ethical considerations. What should the project manager do?

A. Implement a multi-tiered DCA framework.
B. Set up a continuous CUE review process.
C. Establish a comprehensive DPMS protocol.
D. Develop a detailed privacy impact assessment (PIA).

Correct Answer: D

QUESTION 53
An Al project team with a manufacturing company needs to ensure data integrity before moving to model development. They discovered some data inconsistencies due to manual entry errors. What is an effective method that helps to ensure data integrity?

A. Automating data entry processes
B. Implementing real-time data validation rules
C. Using machine learning algorithms to detect and correct errors
D. Conducting regular audits of manually entered data

Correct Answer: B

QUESTION 54
An Al project team has completed an Al go/no-go assessment. They have discovered several technology and data factors to be insufficient. Which action should occur?

A. Verify data quality and stakeholder alignment.
B. Launch the Al project without further assessment.
C. Proceed with development despite data issues.
D. Focus solely on technology upgrades, not data.

Correct Answer: A

QUESTION 55
A project manager is considering the feasibility of an Al solution for a project aimed at improving customer service response times. They need to decide whether the project requirements can be solved with existing technologies or whether Al is the best approach. Which principle does the project manager’s activities represent?

A. Identifying ethical concerns
B. Evaluating cognitive alternatives
C. Assessing scalability requirements
D. Determining automation potential

Correct Answer: B

QUESTION 56
During the business understanding phase, the project manager realizes that the project team has overlooked requirements for the Al model. The model should have a high level of explainability and transparency. What should the project manager do?

A. Define a process for data aggregation and analysis.
B. Develop an algorithm to account for future model adjustments.
C. Revisit the training data for the smart algorithm.
D. Ensure data compliance requirements are clearly documented.

Correct Answer: D

QUESTION 57
A project manager is tasked with overseeing the implementation of an Al model for financial forecasting. They need to ensure the model’s predictions are reliable. If the model’s error rate exceeds acceptable boundaries, what will occur next?

A. Increased stakeholder confidence that the project team will correct
B. Higher than expected computational costs
C. Operationalization delays due to model retraining
D. Reduced need for human oversight since additional Al models will be used

Correct Answer: C

QUESTION 58
During the configuration management of an Al/machine learning (ML) model, the team has observed inconsistent performance metrics across different test datasets. What will cause the inconsistency issue?

A. Low variance in the test results
B. Insufficient model complexity
C. Incorrect data preprocessing steps
D. Overfitting the training data

Correct Answer: C

QUESTION 59
A project manager is reviewing the performance of an Al model used for predictive analytics in sales. The model’s accuracy is within acceptable limits; however, its precision is low. What is the cause for the precision issue?

A. The model is overfitting the training data.
B. The feature selection process is flawed.
C. The training data is unbalanced.
D. The model is underfitting the validation data.

Correct Answer: C

QUESTION 60
A project manager overseeing an Al project is concerned about potential data privacy violations. Before progressing further with the project, what should the project manager do to address this concern?

A. Develop a comprehensive data risk management framework.
B. Conduct a thorough compliance audit against data regulations.
C. Implement real-time monitoring tools for data access control.
D. Establish a cross-functional team to handle data governance.

Correct Answer: B