School Connect Online for Artificial Intelligence (AI) Class 10

Currently School Connect Online is helping students in India and Abroad with their learning for Artificial Intelligence at school level. It is available for students of classes between 6^th to 11^th Standard. CBSE Artificial Intelligence (AI) Syllabus for Class 10

School Connect Online registering schools and students to promote Artificial Intelligence (AI) Program.

And helping students with Online course completion with learning materials, linked free videos and practice question.

Around 2000 students participated in the year of 2019-20,with 75 schools India and Abroad.

The Participating students get course completion certificates and merit students rewarded with certificate of merit and medals.

Students from Participating schools get participation certificate, merit certificate and medals.

Participating Schools for Artificial Intelligence (AI) Olympiad 2019,and also become the front runner in accepting future development of Students in the form of Artificial Intelligence.

Artificial Intelligence (AI) Olympiad Syllabus for Class 10

Objective of AI Curriculum for Class 10th

The objective of Class X AI curriculum – which combines both Inspire and Acquire modules is to develop a readiness for understanding and appreciating Artificial Intelligence and its application in our lives. The curriculum focuses on:

1. Helping learners understand the world of Artificial Intelligence and its applications through games, activities and multi-sensorial learning to become AI-Ready.
2. Introducing the learners to three domains of AI in an age-appropriate manner.
3. Allowing the learners to construct the meaning of AI through interactive participation and engaging hands-on activities.
4. Introducing the learners to AI Project Cycle.
5. Introducing the learners to programming skills –
6. And understanding Advance Pythons and AI
7. Various basics of Python and its coding.

Artificial Intelligence Olympiad 2020-21

Artificial Intelligence Syllabus Class 10

Introduction to Artificial Intelligence, Machine learning and Deep learning.

1. Application of Artificial Intelligence : A look at real life AI implications

• Introduction to AI Domains
• Data Sciences
• Computer Visions
• Natural Language Processing 
• Smart Assistants

2. Ethics of Artificial Intelligence

• Moral Issues : Self driving cars
• Data Privacy
• Artificial Intelligence Bias
• Artificial Intelligence Access

3. Computer Vision

• Introduction of Computer Vision
• Applications of Computer Vision
• Computer Vision : Getting started
• Computer Vision Tasks
• Classification
• Classification + Localisation
• Object detection
• Instance segmentation
• Basics of images
• Basics of Pixels

4. Image features

5. Introduction to OpenCV

6. Convolution

• Task
• Convolution : Explained 

7. Convolution Neural Networks (CNN)

• Introduction
• What is a Convolutional Neural Network?
• Convolution Layer
• Rectified Linear Unit Function
• Pooling Layer
• Fully Connected Layer

8. Natural Language Processing

• Introduction
• Applications of Natural Language Processing
• Natural language processing : Getting started
• Revisiting the AI project cycle

9. Chatbots

• Human Language VS Computer language 
• Arrangement of the words and meaning
• Multiple meanings of a word
• Perfect syntax, no meaning

10. Data Processing

• Text Normalisation
• Bag of words

11. Evaluation

• Introduction
• What is Evaluation?
• Model Evaluation Terminologies
• The Scenario
• Confusion matrix
• Evaluation Methods
• Accuracy
• Precision
• Recall
• Which Metric is important?
• F1 Score

Class 10^th Python for Artificial Intelligence

Chapter 1: Algorithms and Flowcharts

• What is an Algorithm?
  • Activity
  • Challenge Time
  • What is a flowchart?
  • How to Use Flowcharts to Represent Algorithms
  • Test Your Knowledge

Chapter 2: Introduction to Python

• What is a program?
  • What is Python?
  • Why Python for AI?
  • Applications of Python
  • Getting started with Python
    • Downloading and Setting up Python for use
    • Python IDLE installation
  • Run in the Integrated Development Environment (IDE)
    • Interactive Mode
    • Script Mode
  • Python Statement and Comments
    • Python Statement
    • Python Comments
    • Python Keywords and Identifiers
    • Variables and Datatypes
  • Python Operators I
    • Arithmetic Operators
  • Python Input and Output
    • Python Output Using print() function
    • User input
  • Type Conversion
    • Implicit Type Conversion
    • Explicit Type Conversion
  • Python Operators II
    • Comparison operators
    • Logical operators
    • Assignment operators
  • Let’s Practice
  • Test Your Knowledge

Chapter 3 – Introduction to tools for AI

• Introduction to Anaconda
  • How to install Anaconda?
• Jupyter Notebook
  • Introduction
  • What is a Notebook?
  • Installing Jupyter Notebook
  • Working with Jupyter Notebook
  • Notebook Interface – Explained!
• Test Your Knowledge

Chapter 4 – More About Lists and Tuples

• Introduction to Lists
• How to create a list ?
• How to access elements of a list ?
  • List Index
  • Negative Indexing
• Adding Element to a List
  • Using append() method
  • Using insert() Method
  • Using extend() method
• Removing Elements from a List
  • Using remove() method
  • Using pop() method
• Slicing of a List
  • List Methods
• Let’s Practice
• Introduction to Tuples
• How to Create a tuple ?
• Accessing of Tuples
• Deleting a Tuple
• Test Your Knowledge

Chapter 5 – Flow of Control and Conditions

• If Statement
  • If Statement
  • Python if…else Statement
  • Python if…elif…else Statement
  • Syntax of if…elif…else
• Python Nested if statements
• Let’s Practice
• The For Loop
  • Syntax of for Loop
  • Flowchart of for Loop
  • Example: Python for Loop
• The while Statement
  • Syntax of while Loop in Python
• Flowchart of while Loop
• Example: Python while Loop
• Let’s Practice
• Test Your Knowledge

Chapter 6 : Introduction to Packages

• Recap
• Introduction
• What is a package?
  • Package Installation
  • Working with a package
  • What is NumPy?
  • Exploring NumPy!
• Let’s Practice!
• TASK 1
• TASK 2
• Test Your Knowledge

Artificial Intelligence (AI) Olympiad Syllabus brief overview for Class 10^th

Introduction to Artificial Intelligence (AI), Machine learning (ML) and Deep learning.

1. Application of Artificial Intelligence: A look at real life AI implications – With all the excitement and hype about AI that’s “just around the corner” like self-driving cars, instant machine translation,adaptive technology,facial recognition,Optimize Agriculture etc. CBSE Artificial Intelligence(AI) Syllabus for Class 10

It can be difficult to see how AI is affecting the lives of regular people from moment to moment. What are examples of artificial intelligence that you’re already using—right now?

• Introduction to AI Domains
• Data Sciences
• Computer Visions
• Natural Language Processing 
• Smart Assistants

2. Ethics of Artificial Intelligence – A robot vacuum is one thing, but ethical questions around AI in medicine, law enforcement, military defense, data privacy, quantum computing, and other areas are profound and important to consider. One of the primary concerns people have with AI is future loss of job.

Artificial Intelligence (AI) – Issues

• Threat to Privacy. An AI program that recognizes speech and understands natural language is theoretically capable of understanding each conversation on e-mails and telephones.
• Threat to Human Dignity. AI systems have already started replacing the human beings in few industries. …
• Threat to Safety.

More to the ethical issues can be described by following –

• Moral Issues : Self driving cars
• Data Privacy
• Artificial Intelligence Bias
• Artificial Intelligence Access

3. Computer Vision – Optimize your journey to AI from experimentation to production. This comprehensive, proven solution for AI and deep learning simplifies complex operations and reduces your risk.

Assisting humans in identification tasks (to identify object/species using their properties), e.g., a species identification system. Controlling processes (in a way of monitoring robots), e.g., an industrial robot. Detecting events, e.g., for visual surveillance or people counting

• Introduction of Computer Vision
• Applications of Computer Vision
• Computer Vision : Getting started
• Computer Vision Tasks
• Classification
• Classification + Localisation
• Object detection
• Instance segmentation
• Basics of images
• Basics of Pixels

4. Image features – Artificial Intelligence system that processes visual/tangible/pictorial information which usually relies on computer vision, and those capable of identifying specific objects or categorizing images based on their content are performing image recognition.

5. Introduction to OpenCV Python – OpenCV has a modular structure, which means that the package includes several shared or static libraries

6. Convolution

• Task
• Convolution : Explained 

7. Convolutional Neural Networks (CNN) – In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics. They have applications in image and video recognition, recommender systems, image classification, medical image analysis, natural language processing,and financial time series.

• Introduction
• What is a Convolutional Neural Network?
• Convolution Layer
• Rectified Linear Unit Function
• Pooling Layer
• Fully Connected Layer

8. Natural Language Processing – Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.

• Introduction
• Applications of Natural Language Processing
• Natural language processing : Getting started
• Revisiting the AI project cycle

9. Chatbots – A chatbot is a piece of software that conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, although as of 2019, they are far short of being able to pass the Turing test. Chatbots are typically used in dialog systems for various practical purposes including customer service or information acquisition. Some chatbots use sophisticated natural language processing systems, but many simpler ones scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database.

• Human Language VS Computer language 
• Arrangement of the words and meaning
• Multiple meanings of a word
• Perfect syntax, no meaning

10. Data Processing – The Artificial Intelligence and Data Processing program prepares students to work in the areas of design and development of intelligent systems and analysis of big data. These areas are currently undergoing very fast development and are becoming increasingly important. The program leads students to a thorough understanding of basic theoretical concepts and methods. During the study students also solve specific case studies to familiarize themselves with the currently used tools and technologies. Students will thus gain experience that will allow them to immediately use the current state of knowledge in practice, as well as solid foundations, which will enable them to continue to independently follow the developments in the field of Artificial Intelligence

• Text Normalisation
• Bag of words

11. Evaluation

• Introduction
• What is Evaluation?
• Model Evaluation Terminologies
• The Scenario
• Confusion matrix
• Evaluation Methods
• Accuracy
• Precision
• Recall
• Which Metric is important?
• F1 Score

School Connect Online manages “Artificial Intelligence & Robotics Olympiad” for children of class 6th to 11th,with the help of CBSE syllabus of Artificial Intelligence.

For Syllabus of Artificial Intelligence and Robotics Olympiad Click here

CBSE Artificial Intelligence(AI) Syllabus for Class 10

Its India’s first Olympiad Exam which helps students to learn through STEM Education and Experiential Learning, which is an integral part of School Connect Online learning program.

The registered students of Olympiad get free access to learning materials online.

Artificial Intelligence (AI) Syllabus for Class 10 for Olympiad by School Connect Online

Artificial Intelligence (AI) in a Nutshell –

Another word for Artificial Intelligence is Machine Intelligence. The basic definition of Artificial Intelligence (AI) is when machines or computers perform Cognitive Functions that are basically associated with the human brain, for example, thinking, solving problems or learning.

Artificial Intelligence (AI) Jobs In India

India isn’t exactly a hub for cutting-edge research in Artificial Intelligence (AI). There are still misconceptions about the fact that Machine Learning, Data Science, and Artificial Intelligence spell the loss of human jobs, hence the hesitation.

That is probably the reason, India hasn’t spelled out its long-term vision regarding the implementation of Artificial Intelligence.Hence the Job opportunity is immense in AI with new dimensions of career.

CBSE Artificial Intelligence(AI) Syllabus for Class 10

Future Of Artificial Intelligence (AI) In India

As the idea of Artificial Intelligence is getting more and more support, people are seeking to build a career in this field. There is a great scope of AI in India because the aim is to develop a technology-oriented work environment, for efficiency and perfect solutions to different problems. And sooner or later AI is slated to become the part of  our daily life as it has already started.

Introduction School Connect Online –

School connect is an online learning platform, the platform of education which is coming forth every single day to connect students with advanced learning at a low cost.

AI makes it a lot easier for teachers and school management to keep track of how well or poorly the students are performing. Such a system can be used to deal effectively with the vast volume of data and statistics that these schools and colleges normally have. They can use these to create definite reports that help them understand the progress being made by various students. The best part of all this is that such reports can be created as many times as needed. The quality of data can be enhanced well.

Coding and Computer Syllabus Class 1 to 12

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