G7LP-1Introduction to Data Science and AI

Lesson Plan Computer Science Introduction to Data Science and AI Class: Period: Mode: Classroom/Lab Teacher: ____________________________________________________________________________________ Learning Support Assistant: ____________________________________________________________ Time: 80 min. S.M.A.R.T. Learning Objectives By the end of this session, students will be able to: 1. Define the term ‘datification’. 2. Differentiate between structured, semi structured and unstructured data. 3. Define data science. 4. List major benefits of data science. 5. Define the term ‘artificial intelligence’ 6. Explain the 3 domains of AI data, cv, nlp. 7. List applications of AI. 8. Define various types of learning under AI. 9. Explain how data science and AI are related together. Resources Use the eContent to show the animated demos of the lesson. Session Conduction Engage: Ask: How are you identified as a student in school? How are you identified at home? How are you identified when you travel in a train or flight? How are you identified in a restaurant? Let the student come up with the answers. Concept introduction: Inform the students that depending on the context, a person or thing is identified a different set of data. Elaborate on datification using the scenario given in the chapter by giving examples in the give. Explain how data is of three types on the basis of the way it is organised.

Inform that study of data to derive useful information is the main use of data science hence the name. Elaborate on the benefits of data science. Explain that artificial intelligent machines learn from the data. Define the term artificial intelligence on the basis of the above fact. Explain that on the basis of 3 major types of data data, artificial intelligence deals with normal data in data science domain, with visual data in computer vision domain and with natural language data in natural language processing domain. Activity Use Color Picker to understand how orimary colours are mixed to create other colours. Next, explain the main applications of AI: • Predictive smart search • Product recommendation • Fraud detection and prevention • Locations and directions • Sentiment analysis • Object detection • Language processing Then, elaborate how AI is related with machine learning and deep learning. Finally, explain how data science are related with AI as: • Technology to acquire and prepare data sets suitable for AI algorithm. • Technology for developing machine learning applications. Concept Practice: N/A Home Assignments 1. Revise the topic covered. 2. Practice the interactive exercises in Edusoft Smart App. 3. Solve any additional exercises on playground.edusoft.co.in Guided Assignment Students can visit https://youtu.be/RS09Cdz8OMQ Evaluation After completing the lesson solve the exercises given in the book.