AI0-001 AI Implementation and Operations Practice Question
A batch inference pipeline fails intermittently with out-of-memory errors when processing large datasets. The pipeline uses pandas DataFrames and feeds a pre-trained model. Which change would most effectively reduce memory consumption?
⚠ Common exam trap
CompTIA often tests the misconception that scaling up hardware (Option A) is the best solution, when in fact architectural changes like chunking (Option D) are more effective and cost-efficient for batch processing workloads.
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
✓
Split the data into smaller chunks and process sequentially
Splitting a large dataset into smaller chunks and processing them sequentially directly addresses the root cause of the out-of-memory error: the entire dataset is loaded into memory at once via pandas DataFrames. By processing data in batches, each chunk fits within the available RAM, preventing memory exhaustion while still allowing the pipeline to complete the full inference workload.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the instance size of the compute node
Why it's wrong here
This masks the problem but does not address the root cause of high memory usage.
- ✗
Use a database instead of CSV files
Why it's wrong here
Databases do not necessarily reduce memory if the data is still loaded into DataFrames.
- ✗
Convert the model to use half-precision
Why it's wrong here
Half-precision reduces model memory but not data memory, which is the likely bottleneck.
- ✓
Split the data into smaller chunks and process sequentially
Why this is correct
Chunking reduces peak memory by processing subsets of the data at a time.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.