- A
Decrease the event retention period to focus on recent purchases
Why wrong: This would reduce data and likely harm model quality.
- B
Enable the 'others-you-may-like' recommendation type in addition to 'frequently-bought-together'
'Others-you-may-like' uses co-viewed and co-purchased signals, capturing session-level patterns.
- C
Use AutoML Tables to build a custom recommendation model
Why wrong: AutoML Tables is not designed for recommendation systems; it would require significant custom effort.
- D
Set the recommendation type to only 'frequently-bought-together'
Why wrong: This limits to transaction-level co-purchase, not session-level.
- E
Ingest session-level event data (e.g., product views in the same session) into Recommendations AI
Session-level events capture co-viewed items across sessions, improving recommendations.
PMLE Architecting Low-Code ML Solutions Practice Question
This PMLE practice question tests your understanding of architecting low-code ml solutions. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A retail company uses Recommendations AI to power personalized product recommendations on their website. They notice that the 'frequently-bought-together' model is not capturing complementary items that are often purchased in the same session but not necessarily in the same transaction. Which TWO actions should they take to improve the model?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Enable the 'others-you-may-like' recommendation type in addition to 'frequently-bought-together'
To capture cross-session patterns, the company should ensure that user events (including session-level co-occurrence) are properly tracked and ingested. Enabling session-level events and using the 'others-you-may-like' model (which uses co-viewed behavior) can help. Setting the recommendation type to 'frequently-bought-together' does not address session-level data. Reducing event retention would harm model quality.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Decrease the event retention period to focus on recent purchases
Why it's wrong here
This would reduce data and likely harm model quality.
- ✓
Enable the 'others-you-may-like' recommendation type in addition to 'frequently-bought-together'
Why this is correct
'Others-you-may-like' uses co-viewed and co-purchased signals, capturing session-level patterns.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use AutoML Tables to build a custom recommendation model
Why it's wrong here
AutoML Tables is not designed for recommendation systems; it would require significant custom effort.
- ✗
Set the recommendation type to only 'frequently-bought-together'
Why it's wrong here
This limits to transaction-level co-purchase, not session-level.
- ✓
Ingest session-level event data (e.g., product views in the same session) into Recommendations AI
Why this is correct
Session-level events capture co-viewed items across sessions, improving recommendations.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Architecting Low-Code ML Solutions — study guide chapter
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FAQ
Questions learners often ask
What does this PMLE question test?
Architecting Low-Code ML Solutions — This question tests Architecting Low-Code ML Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable the 'others-you-may-like' recommendation type in addition to 'frequently-bought-together' — To capture cross-session patterns, the company should ensure that user events (including session-level co-occurrence) are properly tracked and ingested. Enabling session-level events and using the 'others-you-may-like' model (which uses co-viewed behavior) can help. Setting the recommendation type to 'frequently-bought-together' does not address session-level data. Reducing event retention would harm model quality.
What should I do if I get this PMLE question wrong?
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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