1
Agent
Agent Intelligence (AI) Micro-
Certifications Exam Questions with
Correct Verified Answers, Already
Passed! (Complete & Accurate)
1. Training Data Set - ANS ✓a set of example records for the AI Solution to
"learn" the right way of ticket assignment, classification, and prioritization.
2. Characteristics of a good training set: - ANS ✓Complete
Accurate
Sufficient
3. Precision - ANS ✓The aggregate percentage of correct predictions.
4. Coverage - ANS ✓The aggregate percentage of records that receive the
prediction.
5. Classes - ANS ✓The output field values that the model uses to make
predictions. Each class is an output field value with a list of possible
precisions, coverage, and distribution metrics to choose from.
6. Class Distribution - ANS ✓The percentage of records in the table that
have the output field value.
Agent Intelligence
, 2
Agent
7. Ways to train a solution - ANS ✓Inactive Solutions installed with AI
New Solutions
Active Solutions that are modified
8. Review Solution Statistics: - ANS ✓Estimated Solution Precision
Estimated Solution Coverage
Class Confidence
9. Due Note: 3 - ANS ✓a class record is created for each output field value. A
list of top words is also available per output value.
10. Failed Predictions: - ANS ✓Locate failed predictions by navigating
to:
- ITSM: Incident > Open - Unassigned
- CSM: Customer Service > Cases > Cases Skipped by Agent Intelligence
11. Predictive Model - ANS ✓A trained machine-learning algorithm
used to predict field values during record creation
12. Prediction - ANS ✓An informed guess based on past observations
(historical data)
13. Solution Definition - ANS ✓A configuration record that specifies
how to train a predictive model
Agent Intelligence
Agent
Agent Intelligence (AI) Micro-
Certifications Exam Questions with
Correct Verified Answers, Already
Passed! (Complete & Accurate)
1. Training Data Set - ANS ✓a set of example records for the AI Solution to
"learn" the right way of ticket assignment, classification, and prioritization.
2. Characteristics of a good training set: - ANS ✓Complete
Accurate
Sufficient
3. Precision - ANS ✓The aggregate percentage of correct predictions.
4. Coverage - ANS ✓The aggregate percentage of records that receive the
prediction.
5. Classes - ANS ✓The output field values that the model uses to make
predictions. Each class is an output field value with a list of possible
precisions, coverage, and distribution metrics to choose from.
6. Class Distribution - ANS ✓The percentage of records in the table that
have the output field value.
Agent Intelligence
, 2
Agent
7. Ways to train a solution - ANS ✓Inactive Solutions installed with AI
New Solutions
Active Solutions that are modified
8. Review Solution Statistics: - ANS ✓Estimated Solution Precision
Estimated Solution Coverage
Class Confidence
9. Due Note: 3 - ANS ✓a class record is created for each output field value. A
list of top words is also available per output value.
10. Failed Predictions: - ANS ✓Locate failed predictions by navigating
to:
- ITSM: Incident > Open - Unassigned
- CSM: Customer Service > Cases > Cases Skipped by Agent Intelligence
11. Predictive Model - ANS ✓A trained machine-learning algorithm
used to predict field values during record creation
12. Prediction - ANS ✓An informed guess based on past observations
(historical data)
13. Solution Definition - ANS ✓A configuration record that specifies
how to train a predictive model
Agent Intelligence
