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CBSE Sample Papers with Blueprint & Solutions Class 10 Artificial Intelligence Set 14 (2026–27)

CBSE Sample Papers with Blueprint & Solutions Class 10 Artificial Intelligence Set 14 (2026–27)

Original price was: ₹ 50.00.Current price is: ₹ 29.00.

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Push your board exam preparation to peak performance with Set 14 of the CBSE Class 10 Artificial Intelligence Sample Paper series by Artham Resources. Formulated in direct accordance with the latest CBSE skill-education guidelines, rationalized curriculum, and assessment blueprint for the 2026–27 academic session, this paper provides rigorous practice to test deep conceptual understanding and evaluation accuracy.

CBSE Class 10 Artificial Intelligence Sample Paper with Blueprint & Solutions (2026–27)

Subject Code: 417 | Set 14 | Complete Board Exam Package

Consolidate complex machine learning assessment indicators, Natural Language Processing (NLP) text normalization algorithms, Computer Vision feature representation, and ethical AI deployment for the CBSE Class 10 Artificial Intelligence Board Examination (2026–27) with this full-length model question paper package. Formatted strictly in accordance with CBSE Subject Code 417 and the latest competency-based assessment guidelines, Set 14 strengthens diagnostic skills in resolving confusion matrix edge cases, computing Precision and Recall trade-offs, handling Python data structures, and auditing real-world dataset bias.

Key Product Highlights

  • Full-Length Model Paper (Set 14): Conforms strictly to the official 2-part layout (Part A: Employability Skills and Part B: Subject Specific Skills) comprising Objective Type Questions and Short/Long Descriptive Answers for Class 10 Artificial Intelligence.

  • 100% Stepwise Marking Scheme Solutions: Explicit point-by-point solutions providing exact mathematical derivations (Confusion Matrix calculations, Precision vs. Recall trade-offs, F1 Score formulas), Python code line-by-line outputs, and structured marking rubrics.

  • 50%+ Competency & Inference Focus: Emphasizes scenario-based AI project cycle problem scoping, real-world Natural Language Processing pipeline challenges, Computer Vision pixel analysis, and ethical algorithm governance.

  • Rationalized Syllabus Compliant: Strictly covers both prescribed divisions—Part A: Employability Skills (Communication, Self-Management, ICT, Entrepreneurial, and Green Skills) and Part B: Subject Specific Skills (Introduction to AI, AI Project Cycle, Advance Python, Data Science, Computer Vision, Natural Language Processing, and Model Evaluation).

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