Question 1

In a Convolutional Neural Network, which layer applies a filter to an input image to produce feature maps highlighting different aspects of the image?

Options :

A : Convolutional Layer

B : Fully Connected Layer

C : Pooling Layer

D : Batch Normalization Layer

Answer: A

Question 2

How can ensemble methods improve the robustness of large language models in production environments?

Options :

A : By refining the tokenization process

B : By optimizing the learning rate schedules

C : By increasing the training data size

D : By combining outputs of multiple models

Answer: D

Question 3

Which approach helps in mitigating bias during AI model training?

Options :

A : Increasing the model complexity to handle bias

B : Focusing on high accuracy rather than fairness

C : Applying diverse and representative training datasets

D : Reducing the number of features used in the model

Answer: C

Question 4

What should you focus on when interpreting A/B test results?

Options :

A : Comparing results with similar past experiments only

B : Understanding the statistical significance of the differences

C : Relying on anecdotal evidence from a few users

D : Prioritizing qualitative feedback over quantitative data

Answer: B

Question 5

Which strategy is effective in aligning AI projects with stakeholder expectations?

Options :

A : Focusing on internal team preferences over stakeholder requirements

B : Limiting stakeholder input to avoid conflicting opinions

C : Regularly engaging stakeholders and incorporating their feedback into project planning

D : Making decisions based solely on technical feasibility without stakeholder input

Answer: C

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