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CLASS 10

FACILITATOR HANDBOOK

• Ms. Sharon E. Kumar, Innovation and Education Consultant, Intel AI4Youth Program
• Ms. Ambika Saxena, Intel AI For Youth Coach
• Mr. Bhavik Khurana, Intel AI For Youth Coach
• Mr. Akshay Chawla, Intel AI For Youth Coach
• Mr. Shivam Agrawal, Intel AI For Youth Coach Feedback By:
• Ms. Neelam Roy, ITL Public School, Delhi
• Ms. Mehreen Shamim, TGT, DPS Bangalore East, Bengaluru
• Ms. Saswati Sarangi, PGT Computer Science, RCIS Kalyan Nagar, Bengaluru
• Ms. Aayushi Agrawal, Salwan Girls School, Delhi
• Ms. Isha, HOD Computer Science, Salwan Public School, Delhi Special Thanks To:
• Ms. Indu Khetrapal, Principal, Salwan Public School, Delhi
• Ms. Rekha Vinod, Principal, RCIS Kalyan Nagar, Bengaluru
• Ms. Manilla Carvalho, Principal, Delhi Public School – Bangalore East, Bengaluru
• Ms. Sudha Acharya, Principal, ITL Public School, Delhi
• Ms. Puneet Sardana, Vice-Principal, Salwan Girls School, Delhi

About the book Artificial Intelligence (AI) is being widely recognised to be the power that will fuel the future global digital economy. AI in the past few years has gained geo-strategic importance and a large number of countries are striving hard to stay ahead with their policy initiatives to get their country ready. India’s own AI strategy identifies AI as a n opportunity and solution provider for inclusive economic growth and social development. The report also identifies the importance of skills-based education (as opposed to knowledge intensive education), and the value of project related work in order to “effectively harness the potential of AI in a sustainable manner” to make India’s next generation ‘AI ready’. As a beginning in this direction, CBSE introduced Artificial Intelligence as an optional subject at Class IX from the Session 2019-2020 onwards. Also, to enhance the multidisciplinary approach in teachinglearning so as to sensitize the new generation, it was decided that schools may start AI “Inspire Module” of 12 hours at class VIII itself. CBSE has extended this subject to class X as well from the Session 2020-2021. CBSE is already offering various skill subjects at secondary and senior secondary level to upgrade the skills and proficiency of the young generation and also to provide them awareness to explore various career options. Ai secondary level, a skill subject may be offered as additional sixth subject along with the existing five compulsory subjects. CBSE acknowledges the initiative by Intel India in curating this Facilitator Handbook, the AI training video and managing the subsequent trainings of trainers on the Artificial Intelligence Curriculum. The aim is to strive together to make our students future ready and help them work on incorporating Artificial Intelligence to improve their learning experience. Table of Contents Introduction to AI: Foundational Concepts ........................................................................................ 9 What is Intelligence? ....................................................................................................................... 9 Decision Making ............................................................................................................................ 12 How do you make decisions? .................................................................................................... 12 Make Your Choices! .................................................................................................................. 12 What is Artificial Intelligence? ...................................................................................................... 14 How do machines become Artificially Intelligent? ....................................................................... 14 Applications of Artificial Intelligence around us ........................................................................... 15

Recap ............................................................................................................................................. 42 Recap 1: Jupyter Notebook ....................................................................................................... 42 Introduction to Virtual Environments ....................................................................................... 43 Recap 2: Introduction to Python ............................................................................................... 47 Applications of Python .............................................................................................................. 48 Recap 3: Python Basics .............................................................................................................. 48 Python Packages ........................................................................................................................... 52 Data Sciences .................................................................................................................................... 54 Introduction .................................................................................................................................. 54 Applications of Data Sciences ....................................................................................................... 55 Getting Started .............................................................................................................................. 57 Revisiting AI Project Cycle ......................................................................................................... 57 Data Collection .......................................................................................................................... 62 Data Access ............................................................................................................................... 63 Basic Statistics with Python .......................................................................................................... 66 Data Visualisation ......................................................................................................................... 67 Data Sciences: Classification Model .............................................................................................. 71 Personality Prediction ............................................................................................................... 71 K-Nearest Neighbour: Explained ............................................................................................... 72 Computer Vision ............................................................................................................................... 75 Introduction .................................................................................................................................. 75 Applications of Computer Vision .................................................................................................. 76

Computer Vision: Getting Started ................................................................................................. 78 Computer Vision Tasks .................................................................................................................. 78 Classification ............................................................................................................................. 78 Classification + Localisation ...................................................................................................... 78 Object Detection ....................................................................................................................... 78 Instance Segmentation ............................................................................................................. 78 Basics of Images ........................................................................................................................ 79 Basics of Pixels .......................................................................................................................... 79 Image Features.............................................................................................................................. 84 Introduction to OpenCV ................................................................................................................ 85 Convolution ................................................................................................................................... 86 Convolution : Explained ............................................................................................................ 88 Convolution Neural Networks (CNN) ............................................................................................ 91 Introduction .............................................................................................................................. 91 What is a Convolutional Neural Network? ............................................................................... 92 Convolution Layer ..................................................................................................................... 93 Rectified Linear Unit Function .................................................................................................. 94 Pooling Layer ............................................................................................................................. 95 Fully Connected Layer ............................................................................................................... 96 Natural Language Processing ............................................................................................................ 99 Introduction .................................................................................................................................. 99 Applications of Natural Language Processing ............................................................................. 100

Recall ....................................................................................................................................... 125 Which Metric is Important? .................................................................................................... 126 F1 Score ................................................................................................................................... 127 Introduction to AI: Foundational Concepts

What is Intelligence?

Humans have been developing machines which can make their lives easier. Machines are made with an intent of accomplishing tasks which are either too tedious for humans or are time consuming. Hence, machines help us by working for us, thereby sharing our load and making it easier for us to fulfil such goals. Life without machines today is unimaginable, and because of this, humans have been putting efforts into making them even more sophisticated and smart. As a result, we are surrounded by smart devices and gadgets like smartphones, smartwatches, smart TV, etc. But what makes them smart? For example, how is a smartphone today different from the telephones we had in the last century?

• Images shown here are the property of individual organisations and are used here for reference purpose only.

• Images shown Let us define each term mentioned above to get a proper understanding:

Mathematical • A person's ability to regulate, measure, and understand numerical Logical

Reasoning symbols, abstraction and logic.

Linguistic •Language processing skills both in terms of understanding or Intelligence

implementation in writing or verbally.

Spatial Visual •It is defined as the ability to perceive the visual world and the Intelligence

relationship of one object to another.

Kineasthetic •Ability that is related to how a person uses his limbs in a skilled Intelligence

manilr.

Musical •As the name suggests, this intelligence is about a person's ability to Intelligence

recognize and create sounds, rhythms, and sound patterns.

Intrapersonal •Describes how high the level of self-awareness someone has is. Intelligence

Starting from realizing weakness, strength, to his own feelings.

Existential •An additional category of intelligence relating to religious and Intelligence

spiritual awareness.

Naturalist •An additional category of intelligence relating to

the Intelligence ability to process information on the environment around us.

Interpersonal •Interpersonal intelligence is the ability to communicate with others intelligence

by understanding other people's feelings & influence of the person. But even though one is more skilled in intelligence than the other, it should be noted that in fact all humans have all 9 of these intelligences only at different levels. One might be an expert at painting, while the other might be an expert in mathematical calculations. One is a musician, the other is an expert dancer. In other words, we may define intelligence as:

• Ability to interact with the real world o To perceive, understand and act  Example: Speech Recognition – Understanding and synthesis  Example: Image Recognition  Example: Ability to take action: to have an effect
• Reasoning and planning o Modelling the external world, given input  Solving new problems, planning and making decisions  Ability to deal with unexpected problems, uncertainties
• Learning and adaptation o Continuous learning and adapting graph  Our internal models are always being updated

• Images shown here are the property of individual organisations and are used here for reference purpose only.  Example: Baby learning to categorize and recognise animals For example, if someone starts talking to us, we know how to keep the conversation going. We can understand what people mean and can reply in the same way. When we are hungry, we can come up with various options on what to eat depending upon the food we have at our homes. When we read something, we are able to understand its meaning and answer anything regarding it. While understanding the term intelligence, it must be noticed that decision making comprises of a crucial part of intelligence. Let us delve deeper into it. You’re trapped. All the doors seem to have started shrinking and only one of them leads you out. Which door would you pick?

How do you make decisions?

The basis of decision making depends upon the availability of information and how we experience and understand it. For the purposes of this article, ‘information’ includes our past experience, intuition, knowledge, and self-awareness. We can’t make “good” decisions without information because then we have to deal with unknown factors and face uncertainty, which leads us to make wild guesses, flipping coins, or rolling a dice. Having knowledge, experience, or insights given a certain situation, helps us visualize what the outcomes could be. and how we can achieve/avoid those outcomes.

Make Your Choices!

Scenario 1

You are locked inside a room with 3 doors to move out of the locked room and you need to find a safe door to get your way out. Behind the 1st^ door is a lake with a deadly shark. The 2nd^ door has a mad psychopath ready to kill with a weapon and the third one has a lion that has not eaten since the last 2 months.

Decision Making

• Images shown here are the property of individual organisations and are used here for reference purpose only. Which door would you choose? and Why?

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The answer is gate number 3. The reason being that since the lion has not eaten for 2 months, he wouldn't have survived till now and would already be dead. This makes going out from gate 3 the correct option.

Scenario 2

Aarti invited four of her friends to her House.. They hadn't seen each other in a long time, so they chatted all night long and had a good time. In the morning, two of the friends Aarti had invited, died. The police arrived at the house and found that both the friends were poisoned and that the poison was in the strawberry pie. The three surviving friends told the police that they hadn't eaten the pie. The police asked," Why didn’t you eat the pie ?". Shiv said, " I am allergic to strawberries.". Seema said, " I am on a diet." And Aarti said, "I ate too many strawberries while cooking the pie, I just didn't want anymore." The policemen looked at the pictures of the party and immediately identified the murderer.

• Images shown here are the property of individual organisations and are used here for reference purpose only. Look at the picture and identify who is the murderer? Also state why do you think this is the murderer?

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The answer is Seema, can you guess how the police could tell? It’s because she said she is on a diet and in the picture, she is eating a burger and fries which means she lied. The above scenarios show that it’s the information which helps humans take good decisions. When a machine possesses the ability to mimic human traits, i.e., make decisions, predict the future, learn and improve on its own, it is said to have artificial intelligence. In other words, you can say that a machine is artificially intelligent when it can accomplish tasks by itself - collect data, understand it, analyse it, learn from it, and improve it. You will get to know more about it in the next unit. But, what makes a machine intelligent?

How do machines become Artificially Intelligent?

Humans become more and more intelligent with time as they gain experiences during their lives.

What is Artificial Intelligence?

• Images shown here are the property of individual organisations and are used here for reference purpose only. AI has not only made our lives easier but has also been taking care of our habits, likes, and dislikes. This is why platforms like Netflix, Amazon, Spotify, YouTube etc. show us recommendations on the basis of what we like. Well, the recommendations are not just limited to our preferences, they even cater to our needs of connecting with friends on social media platforms with apps like Facebook and Instagram. They also send us customized notifications about our online shopping details, auto-create playlists according to our requests and so on. Taking selfies was never this fun as Snapchat filters make them look so This isn’t all. AI is also being used to monitor our health. A lot of chatbots and other health apps are available, continuously monitor the physical and mental health of its users. These applications are not limited to smart devices but also vary to humanoids like Sophia, the very first humanoid robot sophisticated enough to citizenship, biometric security systems like the face locks we have in our phones, real-time language translators, weather forecasts, and whatnot! This list is huge, and this module will go on forever if we keep tabulating them. So, take some time, discuss with a friend and identify more and more AI applications around you!

What is not AI?

Since we have a lot of different technologies which exist around us in today’s time, it is very

common for us to misunderstand any other technology as AI. That is why, we need to have a

clear distinction between what is AI and what is not.

which get cool.

• Images shown here are the property of individual organisations and are used here for reference purpose only. As we discussed earlier, any machine that has been trained with data and can make decisions/predictions on its own can be termed as AI. Here, the term ‘training’ is important. A fully automatic washing machine can work on its own, but it requires human intervention to select the parameters of washing and to do the necessary preparation for it to function correctly before each wash, which makes it an example of automation, not AI. An air conditioner can be turned on and off remotely with the help of internet but still needs a human touch. This is an example of Internet of Things (IoT). Also, every now and then we get to know about robots which might follow a path or maybe can avoid obstacles but need to be primed accordingly each time. We also get to see a lot of projects which can automate our surroundings with the help of sensors. Here too, since the bot or the automation machine is not trained with any data, it does not count as AI. Also, it would be valid to say that not all the devices which are termed as "smart" are AI-enabled. For example, a TV does not become AI-enabled if it is a smart one, it gets the power of AI when it is able to think and process on its own. Just as humans learn how to walk and then improve this skill with the help of their experiences, an AI machine too gets trained first on the training data and then optimises itself according to its own experiences which makes AI different from any other technological device/machine. But well, surely these other technologies too can be integrated with AI to provide the users with a much better and immersive experience! Robotics and AI can definitely open the doors to humanoids and self-driving cars, AI when merged with Internet of things can give rise to cloud computing of data and remote access of AI tools, automation along with AI can help in achieving voice automated homes and so on. Such integrations can help us get the best of both worlds!