Podcast
Questions and Answers
How many total questions are there in Part A of the examination?
How many total questions are there in Part A of the examination?
- 6
- 7
- 10
- 11 (correct)
What is the maximum total marks for the subject-specific skills in the examination?
What is the maximum total marks for the subject-specific skills in the examination?
- 40 (correct)
- 30
- 50
- 20
In Part A, how many marks is each objective type question worth?
In Part A, how many marks is each objective type question worth?
- 2 marks
- 3 marks
- 1 mark (correct)
- 4 marks
Which unit has the highest number of total questions in Part A, combining both objective and short answer types?
Which unit has the highest number of total questions in Part A, combining both objective and short answer types?
How many questions must students answer from Part A?
How many questions must students answer from Part A?
Which layer is referred to as the output layer in a neural network?
Which layer is referred to as the output layer in a neural network?
What is the most suitable term for the Indian Government's action of banning apps due to improper data use?
What is the most suitable term for the Indian Government's action of banning apps due to improper data use?
From the following options, which best categorizes the word 'diet' when it appears once in a document?
From the following options, which best categorizes the word 'diet' when it appears once in a document?
Which of the following file formats is commonly used to store data separated by commas?
Which of the following file formats is commonly used to store data separated by commas?
What conclusion can be drawn from the assertion that different individuals can excel in different intelligences?
What conclusion can be drawn from the assertion that different individuals can excel in different intelligences?
How many layers does a typical neural network contain, according to the given statement?
How many layers does a typical neural network contain, according to the given statement?
When stating that 'the better the neural network, the better is the performance', what aspect is being highlighted?
When stating that 'the better the neural network, the better is the performance', what aspect is being highlighted?
What does the term 'stop word' refer to in text processing?
What does the term 'stop word' refer to in text processing?
Which options represent applications that are not driven by AI?
Which options represent applications that are not driven by AI?
Which of the following is considered an application of data science?
Which of the following is considered an application of data science?
What is the process of identifying real-world objects in images or videos called?
What is the process of identifying real-world objects in images or videos called?
Which statement best describes the F1 Score?
Which statement best describes the F1 Score?
What term refers to machines using neural networks to perform tasks with vast amounts of data?
What term refers to machines using neural networks to perform tasks with vast amounts of data?
Which of the following statements about AI output is correct?
Which of the following statements about AI output is correct?
Rajat's predictive model considers which of the following factors?
Rajat's predictive model considers which of the following factors?
Which Chatbot type learns from its environment and experience?
Which Chatbot type learns from its environment and experience?
Which term refers to the process of dividing text into sentences?
Which term refers to the process of dividing text into sentences?
In the context of data classification, which scenario is likely to produce a high false positive cost?
In the context of data classification, which scenario is likely to produce a high false positive cost?
What is the purpose of text normalisation in data processing?
What is the purpose of text normalisation in data processing?
Which option describes 'bag of words' incorrectly?
Which option describes 'bag of words' incorrectly?
What does the term 'resolution' refer to in data analysis?
What does the term 'resolution' refer to in data analysis?
Which of these best describes tokenisation?
Which of these best describes tokenisation?
Which statement about stop words is true?
Which statement about stop words is true?
What does a confusion matrix help to evaluate?
What does a confusion matrix help to evaluate?
How many total marks are allocated for Section A of the question paper?
How many total marks are allocated for Section A of the question paper?
How many questions are students required to answer from Section B?
How many questions are students required to answer from Section B?
What is the total number of questions in the question paper?
What is the total number of questions in the question paper?
What type of questions does Section A contain?
What type of questions does Section A contain?
What is the maximum time allocated to complete the question paper?
What is the maximum time allocated to complete the question paper?
How many different subjects are listed with marks distribution in the question paper?
How many different subjects are listed with marks distribution in the question paper?
Which section has no negative marking?
Which section has no negative marking?
What is the total number of questions that need to be attempted from Section A?
What is the total number of questions that need to be attempted from Section A?
Study Notes
Exam Structure Overview
- Subject: Artificial Intelligence (Subject Code: 417)
- Class: X (Session 2024-2025)
- Total Duration: 2 hours
- Maximum Marks: 50
Part A - Employability Skills (10 Marks)
- Total Questions: 11 (6 objective, 5 short answer)
- Questions to Answer: Any 4 objective, any 3 short answer
- Marks Breakdown:
- Objective Questions: 1 mark each (total 4 marks)
- Short Answer Questions: 2 marks each (total 6 marks)
Part B - Subject Specific Skills (40 Marks)
- Total Questions: 35 (24 objective, 6 short answer, 5 descriptive)
- Questions to Answer: 20 objective, any 4 short answer, any 3 descriptive
- Marks Breakdown:
- Objective Questions: 1 mark each (total 20 marks)
- Short Answer Questions: 2 marks each (total 8 marks)
- Descriptive Questions: 4 marks each (total 12 marks)
Key Topics Covered in Employability Skills
-
Communication Skills - II
- Focus on effective communication techniques
-
Self-Management Skills - II
- Features of self-discipline and organizational skills
-
ICT Skills - II
- Emphasis on technology literacy and its applications
-
Entrepreneurial Skills - II
- Traits and skills necessary for entrepreneurship
-
Green Skills - II
- Awareness of sustainable practices
Key Topics Covered in Subject Specific Skills
-
Introduction to AI
- Basics of Artificial Intelligence concepts and definitions
-
AI Project Cycle
- Steps and processes involved in AI project development
-
Data Sciences
- Techniques and applications in handling data
-
Computer Vision
- Understanding image processing and recognition techniques
-
Natural Language Processing
- Techniques for analyzing and generating human language
-
Evaluation
- Methods for assessing AI models and performance metrics
Question Paper Instructions
- Sections: 2 (Objective and Subjective)
- Total of 21 Questions: 5 + 16 questions categorized into different sections
- Incentives: No negative marking for wrong answers
- Order: Questions must be answered in the prescribed order
Specific Question Examples
- Understanding the difference between AI applications and non-AI applications
- Identifying the consequences of data privacy breaches
- Exploring the terminology around machine learning and neural networks
- Evaluating the implications of different types of false positives in AI
Short Answer and Descriptive Questions
- Engage with practical implications of AI in business and society
- Articulate the importance of goal-setting and effective communication in professional settings
- Analyze human activities leading to environmental issues and how they relate to green skills
Example Question Themes
- AI applications like chatbots and their learning capabilities
- Discussing personal data utilization by apps and ethical considerations
- Exploring machine learning techniques, such as resolution in data processing
Important Concepts to Review
- AI Ethics: The moral principles guiding the use of AI
- Data Privacy: Safeguarding personal information and regulations surrounding it
- Neural Networks: Structure and function in machine learning contexts
- Confusion Matrix: Key metrics for evaluating the accuracy of AI models
Familiarizing with these aspects will enhance readiness for the examination and provide a well-rounded understanding of both employability and subject-specific skills related to Artificial Intelligence.
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Description
Prepare for your Class X Artificial Intelligence exam with this sample question paper designed for the 2024-2025 session. This practice paper focuses on employability skills and includes objective-type and short answer questions to enhance your learning experience.
