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NSCT – Introduction to AI, ML & Data Analytics MCQs

1. . Artificial Intelligence (AI) is:

(A) The simulation of human intelligence in machines that are programmed to think and learn


(B) Encrypting data only


(C) Compressing files only


(D) Backup only



2. . Machine Learning (ML) is:

(A) Backup only


(B) Encrypting algorithms


(C) Compressing code


(D) A subset of AI that allows systems to learn from data and improve performance without explicit programming



3. . Data Analytics involves:

(A) Examining datasets to discover patterns, draw conclusions, and support decision making


(B) Encrypting datasets


(C) Compressing datasets


(D) Backup only



4. . Supervised learning in ML uses:

(A) Encryption keys only


(B) Unlabeled data only


(C) Labeled data to train models to predict outcomes


(D) Backup only



5. . Unsupervised learning in ML uses:

(A) Unlabeled data to identify patterns and groupings


(B) Labeled data only


(C) Encryption data


(D) Backup only



6. . Reinforcement learning in ML involves:

(A) Learning through trial and error with rewards and penalties


(B) Encrypting rewards


(C) Compressing rewards


(D) Backup only



7. . Common applications of AI include:

(A) Backup only


(B) Encrypting files only


(C) Compressing files only


(D) Natural language processing, robotics, image recognition, and autonomous vehicles



8. . Big data analytics helps organizations by:

(A) Backup only


(B) Encrypting big data


(C) Compressing big data


(D) Extracting insights from large and complex datasets to make informed decisions



9. . Feature engineering in ML is:

(A) Compressing features


(B) Encrypting features


(C) The process of selecting, transforming, and creating variables for better model performance


(D) Backup only



10. . Overfitting in ML occurs when:

(A) Encrypting models


(B) A model performs well on training data but poorly on new, unseen data


(C) Compressing models


(D) Backup only



11. . Underfitting occurs when:

(A) Compressing models


(B) Encrypting models


(C) A model is too simple to capture patterns in data


(D) Backup only



12. . AI ethics focuses on:

(A) Compressing ethical data


(B) Encrypting ethical data


(C) Ensuring responsible, fair, and transparent use of AI technologies


(D) Backup only



13. . Predictive analytics uses:

(A) Compression data only


(B) Encryption data only


(C) Historical data to forecast future trends and behaviors


(D) Backup only



14. . Descriptive analytics is used to:

(A) Summarize and interpret historical data


(B) Encrypt data


(C) Compress data


(D) Backup only



15. . Prescriptive analytics helps in:

(A) Encrypting prescriptions


(B) Recommending actions based on data analysis and predictions


(C) Compressing predictions


(D) Backup only



16. . AI and ML require:

(A) Backup only


(B) Encrypting datasets only


(C) Compressing datasets only


(D) Large datasets, computing power, and well-defined algorithms



17. . Natural Language Processing (NLP) is:

(A) AI technology that enables machines to understand, interpret, and generate human language


(B) Encrypting text


(C) Compressing text


(D) Backup only



18. . Key challenges in AI and ML include:

(A) Backup only


(B) Encrypting challenges


(C) Compressing challenges


(D) Data quality, bias, interpretability, and computational cost



19. . Deep learning is:

(A) Backup only


(B) Encrypting networks


(C) Compressing networks


(D) A subset of ML using neural networks with multiple layers for complex pattern recognition



20. . The main purpose of AI, ML, and data analytics is to:

(A) Backup only


(B) Encrypt data only


(C) Compress files only


(D) Automate processes, extract insights, and make data-driven decisions efficiently




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