G8LP-10Introduction to Artificial Intelligence

Lesson Plan - 1 Computer Science Introduction to Artificial Intelligence Topic- Introduction, Human Intelligence & Machines Class: Period: Mode: Classroom/Lab Teacher: ____________________________________________________________________________________ Learning Support Assistant: ____________________________________________________________ S.M.A.R.T. Learning Objectives By the end of this session, students will be able to: 1. Define artificial intelligence. 2. Understand various traits of human intelligence. 3. Explain how we humans learn. 4. Understand how machines should learn. 5. Understand the challenges in the way of machines to become intelligent. Resources Use the eContent to show the animated demos of the lesson wherever required. Session Conduction Engage: Topic being very new, I shall first interact with the students on the following points and questions: • Have you visited internet on computer or mobile phone? • While browsing, do you see advertisements? • The advertisements and notifications are not random. They are mostly relevant to our interests and what we like. If you have made a search for running shoes then later on, when you browse Facebook, you will see the advertisements related with running shoes. Also, while you purchase a running shoe then the Ecommerce web site recommends you the matching products to buy such as socks, different kinds of shoes and sports stuff. How does this happen? How do these web sites come to know what we like or dislike? The answer is – the data we leave online about our moves and interactions with others. This trail of data is very useful for online businesses. Their AI programs can analyse such data of

millions of users like us and profile us according to our preferences and then targeted marketing is done. This process is very powerful since users see most of the items of their preference and chances of buying them increase averagely 20 times. Concept introduction: I will further carry on the discussion with these questions: • Can you share any other instances of intelligent devices or programs or web sites? For example, Facebook blocks fake account or fake news. • Have you heard about Alexa or Cortana or Google Assistant? • Have you heard about driverless cars under development? Well, all these are the examples of artificial intelligence or artificially intelligent devices. Why do we call them artificially intelligent? Because they mimic human intelligence upto some limit. So, how will you define the term artificial intelligence? Then, elaborate on the definition of AI given in the chapter. Discuss about McCarthy and his definition of AI. Concept Demo/Explanation: I shall continue with the question – What does intelligence mean to us? Then I shall discuss sensing and reasoning on the following pointers: • We receive various stimuli through our senses – we see, hear, and feel. • Our senses help us perceive our surroundings. • Our brain analyses the information sensed by us and then with our experience and knowledge, we decide what to do. • How does a machine must sense? – various input devices and sensors. • Analysing the information and deciding the course of action is called reasoning. Reasoning is the evidence that humans are intelligent. • If a machine is able to analyse the data and derive conclusions then it is an intelligent machine. – This is the purpose of artificial intelligence. • Just like humans learn in different ways, a machine may learn from different types of data. A machine learning from financial data will be useful for a bank, a machine learning from images is useful for ecommerce websites, facial recognition applications, smart cameras while a machine learning from human language wil be useful for human interaction with speech and voice such as voice-based search. But the biggest challenge is to make the machines learn like we do. Machines involved in perceiving the surroundings are self-driven cars, robots, smart drones, etc. Machines involved in learning something will need a lot of data about the concerned field. For example, an AI system to diagnose cancer must learn from thousands of records of patients and their medication. Or, a machine learning a game must be exposed to a lot of data about that game in past several years. Machines involved in learning for providing security must be able to recognise friendly people and relatives and should raise alarm for the strangers. Then discuss perception, learning, problem solving, reasoning and language.

Concept Practice: Go to the first URL given at the end of the chapter and read online about AI. Optional Activity: Watch the video in the resources section and discuss it with the teacher. Practical Application: Complete exercise 1 in the Lab Session at the end of the chapter. Home Assignments 1. Revise the topic covered. Evaluation After completing the lesson solve the exercises given at the end of the chapter.

Lesson Plan - 2 Computer Science Introduction to Artificial Intelligence Topic- AI & Neurons, AI Applications Class: Period: Mode: Classroom/Lab Teacher: ____________________________________________________________________________________ Learning Support Assistant: ____________________________________________________________ S.M.A.R.T. Learning Objectives By the end of this session, students will be able to: 1. Understand how human brain works. 2. Understand the terms artificial neurons and artificial neural network. 3. Define machine learning. 4. Differentiate between supervised and unsupervised learning. 5. List at least 6 applications of AI. 6. Understand the significance of AI programming languages R and Python. Resources Use the eContent to show the animated demos of the lesson. Session Conduction Engage: Recall from the previous session and ask the students: • We know how an intelligent machine different from an ordinary machine. • We understand how humans learn and why it is difficult to make machines learn. Concept introduction: Then, I will discuss following points: • Our brain is a set of several interconnected, thousands of processors called neurons. • Neurons retain information and help in recalling the learning as and when required. • If such a network of several interconnected artificial neurons could be made then any machine which will have this brain will become artificially intelligent. Concept Demo/Explanation: The AI field called Machine learning is dedicated to create artificial neural networks for various purposes such as predictions, identification of objects, grouping similar type of data values, devise a move in a game, driving in traffic avoiding obstacle, recognising faces, reading text, processing voice, etc. There are two ways a machine can be intelligent – supervised learning and unsupervised learning.

What is supervised learning? In school, presently, you are learning under the guidance of several teachers but in college and postgraduation you will be learning many concepts on your own. There will be lesser guidance and monitoring. Similarly, if a machine under training is given a lot of data and data us described about what it is; and, also, if the machine is already informed what output it must give then this is called supervised learning. For example, identifying an animal with its picture. But, if a machine under training is given a lot of data and is neither informed what the data is about and output machine must give then this is called unsupervised learning. For example, grouping 10,000 data values into 10 clusters. Then discuss about various applications of AI and programming languages of AI. Concept Practice: Go to the second URL given at the end of the chapter and read online about AI. Optional Activity: Watch the videos from the resources section. Practical Application: Workout the second exercise in the Lab Session. Home Assignments 1. Revise the topic covered. 2. Practice the interactive exercises in Edusoft Smart App. Guided Assignment N/A Evaluation After completing the lesson solve the remaining exercises given at the end of the chapter.