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Question 1

An autonomous drone adjusts its flight path in real time by receiving rewards for efficient navigation and penalties for collisions. Which learning paradigm does this exemplify?

Options :

A : Supervised Learning

B : Unsupervised Learning

C : Semi-Supervised Learning

D : Reinforcement Learning

Answer: D

Question 2

A healthcare AI model trained on adult patient data performs poorly when deployed in pediatric clinics. What fundamental issue does this scenario reveal?

Options :

A : Data normalization failure

B : Overfitting to noisy labels

C : Poor generalization across demographic domains

D : Redundant feature extraction

Answer: C

Question 3

A multinational company deploys a customer service chatbot that frequently fails to respond accurately in non-English languages. What AI adoption challenges are involved in this scenario?

Options :

A : Scalability issues

B : Data quality and preprocessing

C : Language-specific training limitations

D : GPU memory limits

Answer: B,C

Question 4

A financial model uses income and credit score data for predicting loan approval. The income data has values ranging from 20K to 500K, while the credit score data ranges from 300 to 850. What data preprocessing technique is required to handle these features?

Options :

A : Principal Component Analysis (PCA)

B : Imputation for missing data

C : One-hot encoding for both features

D : Feature scaling (standardization or normalization)

Answer: D

Question 5

An AI-powered sentiment analysis tool trained on social media data starts producing extremely biased sentiment predictions after attackers deliberately submit large volumes of manipulated posts with incorrect sentiment labels. What technique is likely being employed?

Options :

A : Adversarial example attack

B : Inference-time evasion

C : Model extraction attack

D : Data poisoning via label corruption

Answer: D