Cognitive project management in AI Exam Questions PDF download

QUESTION: 9

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?

Pick a simple algorithm such as naive bayes
Pick a neural network algorithm since you know this works well for supervised learning approaches
Pick an ensemble method since you're not sure which algorithm will perform best
Pick a simple algorithm such as Gaussian mixture

Answer(s): A

Reveal Solution Next Question

QUESTION: 10

Your team is working on an AI system to provide a more personalized experience for customers on your website.
What should the team do in regard to determining the pattern of AI with regards to the ROI of the project?

First identify the AI pattern you want to use and then figure out the ROI
First determine the pattern of AI you want to use and then work with stakeholders to come up with ROI
First identify the objective you're trying to solve or the ROI you desire and then use that to figure out the correct pattern
First talk to senior managers who set the ROI of the project

Answer(s): C

Reveal Solution Next Question

QUESTION: 11

Clean, well-labeled datasets used for machine learning are partitioned into three subsets: Training sets, Validation sets, and Test sets. As your team is doing this, what's the best way to split up this data?

Split by patterned subsampling
Split by random subsampling
Use the same data for all sets
Split by alphabetical order

Answer(s): B

Reveal Solution Next Question

QUESTION: 12

You need to hire a data scientist to join your team.
What skill sets should you be looking for when hiring and interviewing this person? (Select all that apply.)

Prompt engineering skills
Understanding of tools and technologies for manipulating, collecting, and preparing large data sets
Critical thinking skills
Understanding of algorithms
Automation skills, especially around creating RPA bots
Strong math skills, especially in calculus and statistics

Answer(s): B,C,D,F

Reveal Solution Next Question

QUESTION: 13

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?

Automatic model assessment
Iterative modeling and evaluation
Automatic hyperparameter tuning
Automatic model selection
Automatic algorithm selection

Answer(s): D

Reveal Solution Next Question

QUESTION: 14

One of the key elements of a data-centric methodology is the data requirements phase. During CPMAI Phase II, several unexpected issues have developed and are now threatening the data collection efforts.
What course of action might make the issue worse?

See if you can expand the scope to continue with the project
See if you already have access to enough data to continue with the project
See if you can adjust the scope of this interaction to continue with the project
See if you can purchase the data needed to continue with the project

Answer(s): C

Reveal Solution Next Question

QUESTION: 15

You're testing your model and it is overly sensitive to the fluctuations of data and having trouble generalizing.
What type of problem is this?

You are underfitting the data
You are overfitting the data
You have selected the wrong algorithm
You have selected the wrong data

Answer(s): B

Reveal Solution Next Question

QUESTION: 16

Major factors for the project you are currently working on is around the training time, cost, and complexity of training your models.
Which algorithm is not the best choice given these constraints?

Support Vector Machines (SVM)
Neural Networks
Naive Bayes
Gaussian Mixture

Answer(s): C

Reveal Solution Next Question

PMI Cognitive project management in AI CPMAI Dumps in PDF

Free PMI CPMAI Real Questions (page: 13)

QUESTION: 9

QUESTION: 10

QUESTION: 11

QUESTION: 12

QUESTION: 13

QUESTION: 14

QUESTION: 15

QUESTION: 16