Page 1 :
ARTIFICIAL INTELLIGENCE, CLASS IX, SAMPLE TEST PAPER— 2, ANSWER KEY, Time: 2 Hours, , Max. Marks: 50, , SECTION—A, , PS, , General Instructions:, 1. This question paper consists of two parts viz. Section A: Employability Skills and Section B: Subject Skills., 2. Section A: Employability Skills (10 Marks), i., Answer any 4 questions out of the given 6 questions of 1 mark each., ii., Answer any 3 questions out of the given 5 questions of 2 marks each., 3. Section B: Subject Skills (40 Marks), i., Answer any 10 questions out of the given 12 questions of 1 mark each., ii., Answer any 4 questions out of the given 6 questions of 2 marks each., iii., Answer any 4 questions out of the given 6 questions of 3 marks each., iv., Answer any 2 questions out of the given 4 questions of 5 marks each., 4. This question paper contains 39 questions out of which 27 questions are to be answered., 5. All the questions of a particular part/section must be attempted in the correct order., 6. The maximum time allowed is 2 hours., , Employability Skills: (10 Marks), , KI, , A. Answer any 4 questions out of the given 6 questions of 1 mark each., (1 × 4 = 4), 1. Which of the following is not a method of communication?, a) Verbal communication, b) Non-verbal communication, c) Visual communication, d) Non-visual communication, 2. Which type of parenting prevents a child from developing resilience and coping with stress and failure?, a) Authoritative parenting, b) Both a and b, c) Overprotective parenting, d) None of these, 3. ……………………………. is the ability to use time, energy, and resources effectively to achieve goals., a) Initiative, b) Organisation skill, c) Accountability, d) None of these, 4. Neha wants to send a copy of an e-mail to many people, but she doesn’t want to keep the email addresses visible, to other recipients. In which field should she enter the email addresses?, b) Subject field, a) To field only, c) Cc field, d) Bcc field, 5. The first phase of the entrepreneurship development is …………………………… ., a) Management of the resulting enterprise, b) Development of business plan, c) Identification and evaluation of the opportunity, d) Determination of the required resources, 6. Green economy can lead to …………………………. ., a) New job opportunities, b) Low carbon economy, c) Better quality of life on this planet, d) All of these, B. Answer any 3 questions out of the given 5 questions of 2 marks each., (2 × 3 = 6), 7. List the four elements of effective written communication., The following are the four elements of effective written communication:, • Clear: The message should not be vague or confusing., • Correct: The message should be free of any grammatical and spelling mistakes. Also, the facts mentioned in, the message must be accurate., © Kips Learning Pvt. Ltd 2021

Page 2 :
•, •, , Complete: The message should be complete, i.e., it must include all the relevant information. The complete, message answers most of the questions that receivers might have, thus reducing the need for further, correspondence., Concrete: The content should be supported by facts and figures., , SECTION—B, , PS, , 8. What is SWOT? How is it useful?, SWOT stands for Strength, Weakness, Opportunity, Threat. This analysis is a useful technique for understanding, your strengths and weaknesses. It also helps you in identifying both the opportunities open to you and the, threats or challenges you will possibly face., 9. What is the internet? What are its applications?, Internet is a global system of interconnected computer networks that enables the users to share information, and various resources with each other. It uses common communication standards and interfaces to provide the, physical backbone for a number of interesting applications. Following are some applications of the internet:, • Education, • E-mail, • Media and Entertainment, • Social Networking, 10. What is entrepreneurship? What are the factors that affect the growth of entrepreneurship?, Entrepreneurship is the act of setting up a business and taking on financial risks with the goal of making profit., Factors that affecting entrepreneurship growth are:, • Economic Factors, • Social Factors, • Psychological Factors, 11. Define green economy. What are the aims of green economy?, Green economy is an economy that results in improved human well-being and social equity, while significantly, reducing environmental risks and ecological scarcities. Low carbon growth, Resource efficiency, and Social, inclusion are the aims of green economy., , Subject Skills: (40 Marks), , C. Answer any 10 questions out of the given 12 questions of 1 mark each., , (1 × 10 = 10), , KI, , 12. The nodes of the Artificial Neuron Networks are commonly arranged in ……………….........…...., a. layers, b. random order, c. circles, d. squares, 13. In a decision tree, the starting node is called?, a. Child node, b. Root, c. Leaf node, d. Interior node, , 14. In which of the following learning system do the Artificial Neural Networks do not receive any information, regarding expected outputs?, a. Supervised learning, b. Unsupervised learning, d. Reinforcement learning, c. Forced learning, 15. Which of the following is not an application of NLP?, a. Machine Translation, b. Automatic summarization, c. Text classification, d. Facial Recognition, , 16. Which of the following is not an AI technology?, a. Siri, b. IBM Watson, c. Tesla self-driving cars, d. Conveyor belt, 17. Which of the following systems use decision trees for analysing every possible option choice?, © Kips Learning Pvt. Ltd 2021

Page 3 :
a. Heuristics or rule-based, c. Brute force, , b. Neural Network, d. None of the above, , 18. A ……………….........….... is a decision-making tool that utilizes a graph or model of decisions and their potential, consequences, such as chance event outcomes, resource costs, and utility. (decision tree), 19. The current Artificial Neural Networks are part of ……………….........….... (Weak AI systems), 20. ……………….........….... refers to the data that has a pre-defined data model and which is organized in a predefined way. (structured data), 21. ……………….........….... refers to data that is automatically generated by systems, technologies, or programs. For, example, the list of phone calls made, the logging details on the computer, meta data in emails, etc. (Machine, data), 22. ……………….........….... technology is based on the adaption of how the human brain works (Artificial Neural, , Networks), , PS, , 23. State whether True or False (0.5 Marks each):, a. Microsoft Excel can be used as a tools for Data Visualization, b. Decision Trees can be used for Classification Tasks., D. Answer any 4 questions out of the given 6 questions of 2 marks each., , (True/False), (True/False), (2 × 4 = 8), , 24. Write a short note on Neural Networks., These are one of the techniques or methods of modelling data within the discipline of Artificial Intelligence. This, method tries to mimic or stimulate the working of the human brain. The networks created by this method are, capable of machine learning, i.e. they improve with use., , KI, , 25. What is the difference between MI and AI?, AI and ML are closely related, but these terms aren’t interchangeable. ML actually falls under the umbrella of, AI. It demands that machines carry out tasks in the same way that humans do., , The current application of ML in AI is based around the idea that we should enable access to data so machines, can observe and learn for themselves., , 26. What is meant by Time-stamped data?, This is the data that has time-order in it for defining the sequence. This time order can be based on event time,, i.e. when the data was captured; or, processed time, i.e. when the data was collected. The time stamped data, gains real significance with behavioural data as it helps in creating a true representation of actions over a, period of time. This data helps scientists in creating predictions based or selecting next best action style, models., 27. What is the importance of feedback in a neural network model?, The neural networks learn through an element of feedback. The feedback tells the network if it has made a, mistake or if it has performed correctly. This is the system similar to the system used by animals (including, humans). All the animals learn based on the feedback, which can range from simple to complex. A child, touching fire will learn that the fire is hot and that it has to be avoided., 28. Discuss some real-world applications of computer vision., There are many real-world applications using computer vision:, • Security systems., • Law enforcement systems, for example, matching face of person in criminal database., • Robotics., © Kips Learning Pvt. Ltd 2021

Page 4 :
29. What is the difference between numerical data and textual data?, , As the name suggests this data is related to numbers. This is the data on which mathematical operations, (addition, subtraction, multiplication, etc.) can be performed., Numerical data can further be classified as discrete and continuous data. This is the data made up of characters., These characters can contain numbers too, but we cannot perform calculations on these numbers., E. Answer any 4 questions out of the given 6 questions of 3 marks each., , (3 × 4 = 12), , 30. What’s the difference between strong AI and weak AI?, Strong AI, which can effectively simulate human intelligence, is at the heart of advanced robotics., Weak AI can only predict unique traits that are similar to human intelligence. Alexa and Siri are prime examples, of bad artificial intelligence., • Strong AI has a wide variety of applications., • a wide variety, • Human-level intelligence uses clustering and association to process data., • Weak AI can be excellent at certain basic tasks., • The spectrum can be limited since it employs both supervised and unsupervised learning., , PS, , 31. Explain the problem of bias in real-world data being fed to an AI model., AI system learns from the real-world data fed into it. This means that AI systems can reinforce the biases found, in AI systems. For example, a computer system trained on the data for last 200 years might find that more, females were involved in specific jobs or that more percentage of successful businesses were established by, men and conclude that specific genders are better equipped for handling certain jobs (gender bias)., Understanding or even detecting such biases is not easy because many AI systems act as black boxes. The, reason behind their decision-making is not easy or in some cases, even possible to understand. Many times,, programmers of AI systems themselves cannot explain the logic behind decisions taken by the AI systems., , KI, , 32. Mention some Weak AI systems in existence today.,  Natural Language Processing: The advances in AI technology is helping in advancing the natural language, processing (NLP) capabilities of computer systems, i.e. their ability to understand the natural languages, spoken by human beings.,  Vision systems: AI Systems are helping in many real situations by interpreting and understanding visual data., For example, identifying intrusions in restricted areas, identifying fugitives, smart nannies for protecting, children, etc.,  Speech Recognition: In this area, the AI systems, , 33. Explain the main components of NLP., Natural Language Processing contains two main components:, 1. Natural Language Understanding (NLU): For understanding spoken or written language. This includes:,  establishing linkage with natural language inputs and what they represent.,  analysing different aspects of the language., 2. Natural Language Generation (NLG): For producing meaningful phrases and sentences in the form of natural, language. It involves:,  Text planning: Retrieving relevant text from the data stores,  Sentence planning: Deciding on the correct words, linking them into meaningful phrases, etc.,  Text realisation: Combining phases and words for forming sentences, For AI systems, NLU is much more complicated than NLG. Interestingly, human beings find NLU easier than NLG., 34. How is Artificial Intelligence relevant in robotics?, The field of robotics deals with the construction and programming of robots. Robots are computing machines, that have both hardware and software components. The field of Artificial Intelligence contributes towards the, software component of the robots for answering the challenge of developing robots that can behave and work, like human beings. For example, computer vision helps robots to identify their surroundings. Natural language, © Kips Learning Pvt. Ltd 2021

Page 5 :
processing helps them to communicate more effectively. Neural networks allow them to mimic emotions., Machine learning helps them to learn., 35. Define Data Science., This is a catch-all term for different disciplines related to collecting, managing, and analysing data. All Artificial, Intelligence systems are dependent on data. As such, there is a number of areas in the artificial intelligence, disciplines towards which data science contributes. For example:, Managing Big Data, Data Acquisitions, Data Modelling, Data Analyse, Data Curation, F. Answer any 2 questions out of the given 4 questions of 5 marks each., , (5 × 2 = 10), , KI, , PS, , 36. Mention some AI related careers and the skillsets required for them., Machine Learning Engineer, Understanding of different programming languages, Understanding of applied research and data science., Strong mathematical skills, Data Scientists, Knowledge of Big Data platforms like Hive, Hadoop, MapReduce etc., Knowledge of statistical computing and programming languages like Perl and Python., Strong analytical and communication skills., Business Intelligence Developer, Strong technical and analytical skills, Background in engineering, computer science or related field, Experience of business and markets., AI Research Scientists, Master or Doctorate degree in computer science or related field, Strong background in applied mathematics, 37. Write a short note on the structural classification of data., Every data, no manner its source or form, will have a structure. The difference is in the way the data is, organised, i.e. if it has been organised on the basis of some pre-defined rules, ideas or not., , Based on structures we can classify the data into three types:, , Structured data: This refers to the data that has a pre-defined data model and which is organized in a predefined way. In the past, data structures were pretty simple and often known ahead of the data model design, and so data was typically stored in the tabular row and column format of relational databases. For example, the, train schedule, mark sheets of students from a particular class and school., Unstructured data: This is the data that does not have any pre-defined structure and can take any form. Most of, , the data in the world exists as unstructured data. This data can take any form. For example, videos, audios,, presentations, emails, documents, etc., , Semi-structured data: This is the data whose structure is somewhere between structured and unstructured, data. This data is not organised in a way which makes sense to the relational databases. But it nevertheless has, some sorts of markers and tags that help to give an identifiable structure., 38. Mention some challenges related to Big Data., Big Data is substantially better and more efficient for use with AI systems, but this data is not free from, challenges. The three most prominent challenges of Big Data are:, , © Kips Learning Pvt. Ltd 2021

Page 6 :
 Storage: The development in the technologies is not keeping pace with the increase in the data. Well the, Big Data is……. big. The developments in the IT field is creating technologies and capabilities for storing, this data. But even with these technologies the organisations are struggling to effectively store this data.,  Curation: Storing of Big Data is not enough. This stored data must be relevant for the organisations. This, relevance is achieved through curation of the data. This means organising the data in the manner that makes, meaningful analysis of the data possible. At least 50 percent and many times up to 80 percent time of the, data scientists is spent on curation (or preparation) of the data for usage.,  Pace of Change: Big Data technologies are continuously changing. Until recently Apache Hadoop was the, most popular technology for managing Big Data. Then, Apache Spark was introduced in 2014 and it became the, preferred tool. Now, combination of both Hadoop and Spark is seen as the best approach for handling Big Data., Keeping organisations up-to-date and adopting new technologies are a constant challenge., , KI, , PS, , 39. Explain the concept of artificial neural networks., The concept of ANNs is based on the premise that by making the right connections, the workings of the human, brain can be imitated using silicon and wires as living neurons and dendrites., The human brain is made up of 86 billion nerve cells known as neurons., Axons bind them to thousands of other cells., Dendrites accept stimuli from the external world as well as signals from sensory organs. These inputs produce, electric impulses that pass rapidly through the neural network. A neuron can then forward the message to, another neuron to handle the problem, or it can disregard it., ANNs are made up of several nodes that resemble biological neurons in the human brain. The neurons are, linked together and interact with one another. The nodes will accept input data and perform basic operations, on it. The outcome of these operations is transmitted to other neurons. Each node's output is referred to as its, activation or node value., Each relation has a weight associated with it., ANNs are capable of learning, which is accomplished by varying weight values., There is no need to alter the weights if the network produces a "reasonable or desired" performance. However,, whether the network produces a "bad or undesirable" performance or an error, the algorithm modifies the, weights to maximize subsequent results., , © Kips Learning Pvt. Ltd 2021