Artificial Intelligence Olympiad for Class 11 | Olympiad Online | Coding for Kids
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Artificial Intelligence
Introduction to Artificial Intelligence, Machine learning and Deep learning.
1. Application of Artificial Intelligence : A look at real life AI implications
2. Ethics of Artificial Intelligence
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Moral Issues : Self driving cars
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Data Privacy
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Artificial Intelligence Bias
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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
11. 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
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Artificial Intelligence Olympiad Syllabus brief overview for Class 11th
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Introduction to Artificial Intelligence, Machine learning 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.
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 - 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
11. 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
More Information on School Registration Process of Artificial Intelligence and Robotics Olympiad,follow this link
https://www.schoolconnectonline.com/exam/artificial-intelligence
Register your School in Artificial Intelligence Olympiad –
https://forms.gle/pjErK47j6cV6tsDfA
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