Kips AI Book Class 10 PDF Download: A Comprehensive Guide for CBSE Students
Artificial Intelligence (AI) is one of the most exciting and innovative fields of study in the 21st century. It has applications in various domains such as education, healthcare, entertainment, security, and more. CBSE has introduced AI as a skill subject for class 10 students from the academic session 2020-21. The aim is to equip the students with the basic knowledge and skills of AI and prepare them for the future.
kips ai book class 10 pdf download
One of the best books to learn AI in class 10 is Kips AI Book Class 10. It is a comprehensive and user-friendly book that covers all the topics and concepts of the CBSE syllabus. It also provides ample examples, exercises, projects, and activities to enhance the learning experience of the students. In this article, we will tell you everything you need to know about Kips AI Book Class 10 PDF download. We will also give you some tips and tricks to ace the AI exam using this book. So, let's get started!
What is Kips AI Book Class 10?
An overview of the book and its features
Kips AI Book Class 10 is a book written by Kips Learning Solutions, a leading publisher of computer books for school students. It is based on the latest CBSE syllabus and guidelines for AI skill subject. The book has two parts:
Part-A: Employability Skills, which covers topics such as communication skills, self-management, information and communication technology, entrepreneurial skills, and green skills.
Part-B: Subject Specific Skills, which covers topics such as introduction to AI, AI project cycle, advance Python, data science, computer vision, natural language processing, and evaluation.
The book has many features that make it an ideal choice for learning AI in class 10. Some of them are:
The book is written in simple and lucid language for easy understanding.
The book has colorful illustrations, diagrams, charts, and tables to explain the concepts visually.
The book has numerous examples, exercises, projects, and activities to reinforce the concepts and develop practical skills.
The book has a solution section at the end of each chapter to help the students check their answers and clear their doubts.
The book has a glossary section at the end of the book to help the students learn the important terms and definitions related to AI.
Why is it important to study AI in class 10?
AI is not just a subject, but a skill that can help you in many ways in your academic and professional life. Some of the reasons why you should study AI in class 10 are:
AI can help you develop your logical thinking, problem-solving, creativity, and innovation skills.
AI can help you explore various domains and careers that use AI such as education, healthcare, entertainment, security, and more.
AI can help you learn about the latest technologies and trends that are shaping the world.
AI can help you prepare for the future challenges and opportunities that AI will bring.
Therefore, studying AI in class 10 can give you a competitive edge and a lifelong learning attitude.
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How to download Kips AI Book Class 10 PDF for free?
The official CBSE website
The easiest and most reliable way to download Kips AI Book Class 10 PDF for free is to visit the official CBSE website. Here are the steps to follow:
Go to the CBSE website at .
Click on the "Curriculum" tab and select "Secondary Curriculum (IX-X)" from the drop-down menu.
Scroll down to the "Skill Subjects" section and click on "Artificial Intelligence (Code No. 417)".
You will see a list of documents related to the AI subject. Click on the link that says "Artificial Intelligence - Class X - Session 2020-21 - Kips Publication".
A new window will open with the PDF file of Kips AI Book Class 10. You can view it online or download it to your device by clicking on the download icon at the top right corner of the window.
Other online sources
Another way to download Kips AI Book Class 10 PDF for free is to use other online sources that provide free e-books. However, you should be careful while using these sources as they may not be authorized or updated. Some of the online sources that you can try are:
: This is a search engine that lets you find and download millions of PDF files for free. You can search for Kips AI Book Class 10 and download it from the results.
: This is a website that provides free NCERT books and solutions for all classes and subjects. You can also find CBSE books and guides for skill subjects such as AI. You can search for Kips AI Book Class 10 and download it from the results.
: This is a website that provides free study material, notes, worksheets, sample papers, and previous year papers for CBSE students. You can also find CBSE books and guides for skill subjects such as AI. You can search for Kips AI Book Class 10 and download it from the results.
Tips and precautions for downloading
While downloading Kips AI Book Class 10 PDF for free, you should keep in mind some tips and precautions to avoid any problems or errors. Some of them are:
Make sure you have a stable internet connection and enough storage space on your device.
Make sure you have a PDF reader software or app installed on your device to open and view the file.
Make sure you download the file from a trusted and updated source that matches the CBSE syllabus and guidelines.
Make sure you scan the file for any viruses or malware before opening it.
Make sure you do not share or distribute the file without proper permission or credit.
What are the contents of Kips AI Book Class 10?
Part-A: Employability Skills
This part of the book covers five topics that aim to develop the employability skills of the students. These skills are essential for any career or profession in the modern world. The topics are:
S.No.TopicDescription
1Communication Skills-IIThis topic covers various aspects of communication such as listening, speaking, reading, writing, presentation, and interpersonal skills. It also covers topics such as email etiquette, formal and informal communication, and barriers to communication.
2Self-Management-IIThis topic covers various aspects of self-management such as self-awareness, self-esteem, self-confidence, self-motivation, goal setting, time management, stress management, and coping skills. It also covers topics such as emotional intelligence, resilience, and positive attitude. 3Information and Communication Technology-IIThis topic covers various aspects of information and communication technology such as internet, web, social media, online safety, digital citizenship, and cyber ethics. It also covers topics such as online collaboration, cloud computing, and artificial intelligence.
4Entrepreneurial Skills-IIThis topic covers various aspects of entrepreneurial skills such as innovation, creativity, opportunity recognition, risk taking, decision making, and resource management. It also covers topics such as business plan, marketing, finance, and legal aspects.
5Green Skills-IIThis topic covers various aspects of green skills such as environmental awareness, sustainability, renewable energy, waste management, and green jobs. It also covers topics such as climate change, biodiversity, and carbon footprint.
Part-B: Subject Specific Skills
This part of the book covers seven topics that aim to develop the subject specific skills of the students. These skills are related to the core concepts and applications of AI. The topics are:
S.No.TopicDescription
1Introduction to AIThis topic covers the basics of AI such as definition, history, types, applications, advantages, and disadvantages. It also covers topics such as AI agents, environments, problems, and solutions.
2AI Project CycleThis topic covers the steps involved in an AI project cycle such as problem identification, data collection, data preprocessing, data analysis, model building, model testing, model deployment, and model evaluation. It also covers topics such as tools and platforms for AI projects.
3Advance PythonThis topic covers the advanced features of Python programming language such as functions, modules, packages, classes, objects, inheritance, polymorphism, exception handling, file handling, and database connectivity. It also covers topics such as libraries and frameworks for AI such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, and Keras.
4Data ScienceThis topic covers the concepts and techniques of data science such as data types, data structures, data visualization, data manipulation, data analysis, data mining, and data modeling. It also covers topics such as statistics, probability, hypothesis testing, correlation, regression, classification, clustering, and association rules.
5Computer VisionThis topic covers the concepts and techniques of computer vision such as image processing, image segmentation, image enhancement, image recognition, face detection, face recognition, object detection, object recognition, and optical character recognition. It also covers topics such as convolutional neural networks, transfer learning, and image augmentation.
6Natural Language ProcessingThis topic covers the concepts and techniques of natural language processing such as text processing, text analysis, text summarization, text generation, sentiment analysis, text classification, text translation, speech recognition, speech synthesis, and chatbots. It also covers topics such as natural language understanding, natural language generation, and recurrent neural networks.
7EvaluationThis topic covers the methods and metrics for evaluating the performance and accuracy of AI models such as confusion matrix, accuracy, precision, recall, f1-score, roc curve, auc score, mse, rmse, mae, r2 score, and cross-validation. It also covers topics such as overfitting, underfitting, bias-variance trade-off, regularization, and hyperparameter tuning.
How to prepare for the AI exam using Kips AI Book Class 10?
Tips and strategies for effective learning
To prepare well for the AI exam using Kips AI Book Class 10, you should follow some tips and strategies that can help you learn the concepts and skills effectively. Some of them are:
Read the book thoroughly and understand the concepts with the help of examples and illustrations.
Practice the exercises and projects given at the end of each chapter to apply the concepts and skills in real-world scenarios.
Revise the important terms and definitions given in the glossary section at the end of the book.
Solve the sample questions and answers given in the solution section at the end of each chapter to check your understanding and clear your doubts.
Refer to other online resources such as videos, tutorials, blogs, podcasts, and courses to learn more about AI and its applications.
Form a study group with your classmates or friends and discuss the topics and doubts with them.
Take mock tests and practice papers to assess your preparation level and identify your strengths and weaknesses.
Review your mistakes and feedback and work on improving them.
Sample questions and answers from the book
To give you an idea of the type and level of questions that you can expect in the AI exam, we have selected some sample questions and answers from the book. You can find more questions and answers in the solution section at the end of each chapter.
Question 1: What are the three types of AI agents?
Answer: The three types of AI agents are:
Simple reflex agents: These are the simplest kind of AI agents that act based on the current percept (sensory input) without considering the history or the future. They have a fixed set of rules or condition-action pairs that determine their actions. For example, a vacuum cleaner robot that moves away from the wall when it senses a bump.
Model-based reflex agents: These are AI agents that act based on the current percept as well as a model of the world that they maintain internally. They use the model to keep track of the state of the world and update it based on their actions and observations. They also have a set of rules or condition-action pairs that determine their actions. For example, a chess-playing agent that uses a model of the board and the rules of the game to decide its moves.
Goal-based agents: These are AI agents that act based on the current percept, a model of the world, and a goal that they want to achieve. They use the model to predict the outcomes of their actions and choose the action that brings them closer to their goal. They also have a set of rules or condition-action pairs that determine their actions. For example, a taxi driver agent that uses a model of the city and a goal of reaching a destination to decide its route.
Question 2: What are the steps involved in data preprocessing?
Answer: Data preprocessing is the process of transforming raw data into a suitable format for data analysis and modeling. It involves the following steps:
Data cleaning: This step involves removing or correcting any errors, inconsistencies, outliers, missing values, or duplicates in the data.
Data integration: This step involves combining data from multiple sources or formats into a single data set.
Data transformation: This step involves changing the scale, range, type, or distribution of the data to make it more suitable for analysis or modeling.
Data reduction: This step involves reducing the size or complexity of the data by using techniques such as sampling, aggregation, dimensionality reduction, or feature selection.
Data discretization: This step involves converting continuous data into discrete or categorical data by using techniques such as binning, clustering, or encoding.
Question 3: What are the differences between supervised and unsupervised learning?
Answer: Supervised and unsupervised learning are two types of machine learning methods that differ in the following aspects:
AspectSupervised LearningUnsupervised Learning
DataThe data has input features and output labels.The data has only input features and no output labels.
TaskThe task is to learn a function that maps the input features to the output labels.The task is to discover patterns, structures, or groups in the input features.
ExamplesSome examples of supervised learning are regression, classification, and prediction.Some examples of unsupervised learning are clustering, dimensionality reduction, and anomaly detection.
EvaluationThe evaluation is done by comparing the predicted output labels with the actual output labels using metrics such as accuracy, precision, recall, etc.The evaluation is done by measuring the quality of the patterns, structures, or groups using metrics such as silhouette score, davies-bouldin index, etc.
Conclusion
In this article, we have given you a comprehensive guide on Kips AI Book Class 10 PDF download. We have covered the following topics:
What is Kips AI Book Class 10 and why is it important to study AI in class 10?
How to download Kips AI Book Class 10 PDF for free from the official CBSE website and other online sources?
What are the contents of Kips AI Book Class 10 and how are they divided into two parts?
How to prepare for the AI exam using Kips AI Book Class 10 and what are some tips and strategies for effective learning?
What are some sample questions and answers from the book that can help you practice and revise the concepts and skills?
We hope that this article has helped you understand and appreciate the value of Kips AI Book Class 10. We also hope that it has motivated you to learn AI in class 10 and explore its applications in various domains. We wish you all the best for your AI exam and your future endeavors!
FAQs
Q1: Where can I buy a hard copy of Kips AI Book Class 10?
A1: You can buy a hard copy of Kips AI Book Class 10 from any online or offline bookstore that sells CBSE books. You can also order it from the official website of Kips Learning Solutions at .
Q2: How many marks are allotted for the AI skill subject in class 10?
A2: The AI skill subject in class 10 has a total of 100 marks, out of which 50 marks are for theory and 50 marks are for practical. The theory exam has two sections: Part-A (Employability Skills) for 10 marks and Part-B (Subject Specific Skills) for 40 marks. The practical exam has three components: Lab Activities for 30 marks, Project Work for 15 marks, and Viva Voce for 5 marks.
Q3: How can I get more practice papers and previous year papers for the AI exam?
A3: You can get more practice papers and previous year papers for the AI exam from various online sources such as , etc. You can also refer to some books and guides such as Oswaal CBSE Question Bank Class 10 Artificial Intelligence Book or Arihant All In One Artificial Intelligence CBSE Class 10.
Q4: What are some other books or resources that I can use to learn AI in class 10?
A4: Some other books or resources that you can use to learn AI in class 10 are:
Coding with Python by Sumita Arora (Dhanpat Rai Publications)
Data Science for Beginners by Andrew Park (Independently Published)
Machine Learning for Kids by Dale Lane (Independently Published)
Coursera's Introduction to Artificial Intelligence (AI) course by IBM ()
Khan Academy's Introduction to AI and Machine Learning course ()
Google's AI Education website ()
Q5: What are some of the career options or opportunities that I can pursue after learning AI in class 10?
A5: Learning AI in class 10 can open up many career options or opportunities for you in the future. Some of them are:
AI Engineer: An AI engineer is a professional who designs, develops, tests, and deploys AI systems and applications using various tools and frameworks.
Data Scientist: A data scientist is a professional who analyzes, interprets, and visualizes large and complex data sets using various methods and techniques.
Machine Learning Engineer: A machine learning engineer is a professional who builds, trains, and optimizes machine learning models using various algorithms and libraries.
Natural Language Processing Engineer: A natural language processing engineer is a professional who works with natural language data such as text and speech using various methods and techniques.
Computer Vision Engineer: A computer vision engineer is a professional who works with image and video data using various methods and techniques.
AI Researcher: An AI researcher is a professional who conducts original and innovative research in the field of AI using various methods and techniques.
AI Educator: An AI educator is a professional who teaches and mentors students and learners about the concepts and skills of AI using various methods and techniques.
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