Question 1

A real estate agency uses a model to estimate property prices based on features like location, square footage, and number of rooms. What type of model is being used?

Options :

A : Classification

B : Association rule mining

C : Clustering

D : Regression

Answer: D

Question 2

A financial services company is developing an AI-powered credit scoring system. The model needs to classify customers into low-risk, medium-risk, and high-risk categories based on historical financial data. Which type of AI learning should be used?

Options :

A : Supervised Learning, as it utilizes labeled data to train the model on past credit scores and customer profiles

B : Federated Learning, since it allows multiple institutions to train the model without sharing sensitive data

C : Unsupervised Learning, as it does not require historical labels for training

D : Deep Learning, as it requires large-scale neural networks to process customer financial history

Answer: A

Question 3

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 4

A dataset contains a feature with 100 categories, but only 5 samples are available for each category. What potential issue could arise when training a model on this dataset?

Options :

A : Data imbalance

B : Data normalization

C : Underfitting

D : Overfitting

Answer: A

Question 5

A large e-commerce platform adopts AI to continuously analyze build pipeline telemetry and recommend changes in build parallelization strategy. What AIOps capability does this reflect?

Options :

A : VPN tunneling automation

B : Immutable infrastructure enforcement

C : Continuous optimization of operational workflows

D : Static resource provisioning

Answer: C

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