Artificial Intelligence For Kids

Learn to build & code AI models using Scratch

What you'll learn
Define and understand the meaning of AI and machine learning and explore their applications
Explore the different types and techniques in AI
Explore Machine Learning and how it works
Differentiate between various Machine Learning types
Implement different Machine Learning Algorithms
Develop Machine Learning programs in various areas.
Requirements
Basic scratch knowledge
Description
What is Artificial Intelligence? How does it impact our daily life? How to create Machine Learning models?…. In this course, we will answer all of those questions and many more while teaching you how to implement simple ML models for the real world using Scratch!Through this course you will develop your skills and knowledge in the following areas:The concept of Artificial Intelligence, when and how it started.The different types and techniques in AIExplore Machine Learning and how it worksDifferentiate between different Machine Learning typesExplore Machine Learning AlgorithmsDevelop Machine Learning programs in various areasBuild a variety of AI systems and models.how Machine learning can be used to make software and machines more intelligent.Differentiate between supervised learning and unsupervised learning Differentiate between Classification and Regression How chatbots are created Detailed course outline: Introduction to AI - Overview on history and Fields of AI:- Explore AI activities and games- Programming and AI - What is programming - Create and code a shooting gameArtificial Intelligence Applications- Explore different AI applications - Explore different AI branches - Create and code an advanced shooting gameIntroduction to Machine Learning -  Overview of Machine Learning -  Explore Ai game that uses Machine Learning - Differentiating between Machine Learning models- develop a smart game using machine learning algorithms with Scratch Introduction to supervised learning - Overview of supervised learning - Explore an AI game that uses a supervised learning algorithm - Differentiating between classification and regression - create a smart classroom project using scratch Introduction to Classification - taking a look into Classification applications - Explore AI  activity that uses classification - Learn about confidence threshold - Project: create a model that can differentiate between Cats, Dogs and DucksText Classification- Overview of Text classification - Explore how chatbots are created - learn about Sentiment Analysis- Project: create a chatbot  checkpoint - summary of previous classes- Take a mid-course quiz - Project: sort different vegetables and fruits in the fridge based on their categoryIntroduction to datasets and regression - What is data - What is regression - Explore a regression activity Introduction to decision trees - Overview of decision trees - Explore decision trees applications- Project: create a Tic Tac Toe game using the decision trees algorithm - Inspect the Decision tree structure - what is Pruning and why do we need it while applying decision trees - Project: create a Pac-Man game using decision trees AI activities - Interact with different AI activities ( Music, Pac-Man,  POGO,….) AI Applications and Course Summary- Summary of the course - Explore advanced ai applications - End-of-course assessment - Develop an advanced AI chatbot

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 AI Activity

Lecture 3 AI and Programming

Lecture 4 What is programming

Lecture 5 Class Project: Shooting game part 1

Lecture 6 Conclusion

Section 2: Artificial Intelligence

Lecture 7 AI applications

Lecture 8 Artificial Intelligence Branches

Lecture 9 Class Project: Shooting game part 2

Lecture 10 Conclusion

Section 3: Machine Learning

Lecture 11 Introduction to Machine Learning

Lecture 12 What is Machine Learning

Lecture 13 AI Activity-2

Lecture 14 Types of Machine Learning

Lecture 15 How to create a project in ML for kids

Lecture 16 Class Project: Rock Paper Scissors

Lecture 17 Conclusion

Section 4: Supervised Learning

Lecture 18 Introduction to Supervised learning

Lecture 19 What is Supervised Learning?

Lecture 20 AI Activity: Thing Translator

Lecture 21 Activity Explanation

Lecture 22 Classification vs Regression

Lecture 23 Class Project: Smart Classroom

Lecture 24 conclusion

Section 5: Classification

Lecture 25 Introduction to Classification

Lecture 26 Classification Applications

Lecture 27 AI Activity: Hand Track

Lecture 28 Activity Explanation

Lecture 29 Confidence Threshold

Lecture 30 Class Project: Cat, Dog and Duck

Lecture 31 Conclusion

Section 6: Chatbots

Lecture 32 Text Classification

Lecture 33 Activity: Mitsuku

Lecture 34 Sentiment Analysis

Lecture 35 Class Project: Chatbots

Lecture 36 Conclusion

Section 7: Checkpoint!

Lecture 37 Summary of Previous Classes

Lecture 38 Mid Course Project

Section 8: Datasets and Regression

Lecture 39 Introduction to datasets and regression

Lecture 40 What is Data?

Lecture 41 Regression

Lecture 42 Activity: Regression

Lecture 43 Conclusion

Section 9: Decision Trees

Lecture 44 Introduction to Decision Trees

Lecture 45 What's a Decision tree?

Lecture 46 Decision Trees Applications

Lecture 47 Activity: Akinator

Lecture 48 Class Project: Tic Tac Toe

Lecture 49 Conclusion

Section 10: Decision Trees Continued

Lecture 50 Decision Tree Structure

Lecture 51 Activity: Decision Trees

Lecture 52 Pruning

Lecture 53 Class Project: Pac Man

Lecture 54 Conclusion

Section 11: AI Activities

Lecture 55 Introduction to AI activities

Lecture 56 Activity: AI Music

Lecture 57 Activity: POGO Kids!

Lecture 58 Activity: PacMan

Lecture 59 Project: Open Project

Lecture 60 Conclusion

Section 12: AI Applications and Course Summary

Lecture 61 Introduction

Lecture 62 Summary

Lecture 63 AI Applications

Lecture 64 Final Project: AI Chatbot

Lecture 65 Course Conclusion

Passionate kids who are interested in learning AI,kids and beginners who want to learn more about AI,Anyone new to AI who doesn't know where to start