CBSE Class 10 Artificial Intelligence Question Paper 2026 PDF Download

The Artificial Intelligence course (Subject Code 417) is a technical elective that introduces the fundamental concepts of machine learning, data science, and neural networks. The 2026 examination followed a structured two-hour format designed to test both theoretical understanding and practical application of the AI project cycle. Accessing this paper provides you with a clear benchmark for the difficulty level and the competency-based questions favored by the board.

Examination Structure and Pattern

The theory paper carries a maximum of 50 marks and is structured into two main sections. Students are allotted 2 hours to complete the examination:

• Section A: Objective Type Questions (24 Marks): This section contains 5 questions designed to test your core conceptual clarity. These questions are objective in nature, focusing on definitions, terminology, and basic logical reasoning within the context of AI.
• Section B: Subjective Type Questions (26 Marks): This section contains 16 questions, out of which you are required to answer 10. These questions vary in length and depth, covering the following key areas:
• Employability Skills: Communication, self-management, ICT, entrepreneurial, and green skills.
• AI Project Cycle: Revisiting problem scoping, data acquisition, data exploration, and evaluation.
• Advanced Modeling: Supervised, unsupervised, and reinforcement learning approaches.
• Domains of AI: Deep dives into Computer Vision, Natural Language Processing (NLP), and statistical data analysis.
• Ethical Frameworks: Understanding AI ethics, bias, and the impact of technology on society and sustainable development.

How to Use This Paper for Preparation

1. Timed Practice: Given the 2-hour limit, practice solving the entire paper in one sitting. This helps you balance your time between the objective questions and the detailed subjective answers.
2. Focus on the AI Project Cycle: A significant portion of the paper is dedicated to the project cycle. Ensure you can describe the stages of scoping, data exploration, and modeling with precision.
3. Master Technical Terminology: Use this paper to test your recall of specific terms like "Convolutional Neural Networks," "Train-test split," "Accuracy vs. Error rate," and "Lexical Analysis." Accuracy in terminology is essential for securing full marks in subjective questions.
4. Practice Case Studies: Many questions in the subjective section are based on real-world scenarios. Use the provided paper to practice applying concepts like classification, regression, or clustering to specific business or technical cases.
5. Section Management: The paper requires you to attempt questions in the correct order within their respective sections. Use your practice time to habituate yourself to this organizational requirement, as it ensures a smooth evaluation process.

Recommended Study Approach

To get the most utility from this resource, treat it as a mock test. When writing your subjective answers, use bullet points for clarity. For questions requiring numerical calculation—such as finding the accuracy and error rate of a model—show your steps clearly, as marks are awarded for the process, not just the final result. Comparing your responses against standard academic guidelines will help you identify areas where your conceptual understanding needs further reinforcement, allowing you to enter the exam with full confidence.