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ISQI ISTQB Certified Tester Testing with Generative AI (CT-GenAI) v1.0 Sample Questions:

1. Which statement about fine-tuning for test tasks is INCORRECT?

A) It replaces the model's general knowledge entirely and prevents overfitting
B) It enhances relevance to organizational terminology and formats
C) It adapts a pre-trained model to a domain using task-specific data
D) It can be applied to smaller SLMs to improve task performance with lower compute

2. Which setting can reduce variability by narrowing the sampling distribution during inference?

A) Using a larger context window
B) Lowering temperature
C) Increasing temperature
D) Increasing learning rate

3. Which technique MOST directly reduces hallucinations by grounding the model in project realities?

A) Randomize prompts each run
B) Rely on generic examples only
C) Use longer temperature settings
D) Provide detailed context

4. What BEST protects sensitive test data at rest and in transit?

A) Rely on obfuscation instead of encryption
B) Use public file shares with read-only links
C) Disable TLS and rely on VPN only
D) Enforce role-based access controls

5. You are using an LLM to assist in analyzing test execution trends to predict potential risks. Which of the following improvements would BEST enhance the LLM's ability to predict risks and provide actionable alerts?

A) Expand the output format to include risk predictions with severity levels, recommended actions, and a timeline for team intervention based on trend analysis.
B) Add an instruction to calculate statistical variance and highlight tests that deviate by more than 20% from baseline metrics.
C) Emphasize constraints that focus on deviations that could impact release timelines or quality gates.
D) Specify that the role is a test analyst with expertise in predictive analytics and risk management.

Solutions: