AI Essentials: Introduction to Artificial Intelligence

AI Essentials: Introduction to Artificial Intelligence, available at $19.99, has an average rating of 4.2, with 20 lectures, 1 quizzes, based on 309 reviews, and has 22100 subscribers.

You will learn about AI, it's Modern History and current Implementations Machine Learning Neural Networks and Deep Learning The relationship between Machine Learning, Neural Networks and Deep Learning The theory of Artificial General Intelligence (AGI) Intelligent agents Natural Language Processing (NLP) Computer Vision AI Ethics AI In Robotics Search Algorithms Knowledge Representation and Reasoning (KRR) Explain-ability and Transparency in AI (XAI) Generative Artificial Intelligence (GenAI) Large Language Models (LLMs) AI and IT AI for Good This course is ideal for individuals who are No specific requirements. The course is for any individual who want to build a career in AI and data science or improve their knowledge. or What is AI? AI is a field of computer science that studies how to create machines that can process information, make decisions, and perform specific tasks. or The History of modern AI. The field of artificial intelligence (AI) has a long and rich history, dating back to the early days of computing. However, the field as we know it today was founded in 1956 at a conference at Dartmouth College in New Hampshire. This conference brought together the leading researchers in AI at the time, including Alan Turing, John McCarthy, and Marvin Minsky. The conference is credited with helping to define the field of AI and to set the agenda for future research. or Artificial Intelligence “AI” is a complex field that needs the ability of people from diverse disciplines to work together. As an example, manufacturing autonomous vehicles like self-driving cars requires the work of people from different fields, such as AI Researchers, Automotive Engineers, and Computer Vision Researchers. AI Researchers develop algorithms that enable self-driving cars to perceive their surroundings, make decisions, and control their movements. Automotive Engineers develop the hardware and software systems that are needed to implement these algorithms, and Computer Vision Researchers develop new techniques for enabling self-driving cars to see and understand the world. or What is Machine Learning? Machine Learning is a type of Artificial Intelligence (AI) that allows computers to learn from data without explicit programming. In other words, machine learning algorithms can recognize patterns and make predictions based on data, without getting a command. This enables computers to learn new tasks and improve their performance over time without human intervention. or Where is Machine Learning used? Machine learning is in use by a wide range of applications, including email filtering, Social Media Personalization, Image Recognition, Speech Recognition, fraud detection, Text prediction, Product recommendation, medical diagnosis, Healthcare Personalization, Traffic Prediction. or Neural networks are a type of machine learning algorithm that is inspired by the structure and function of the human brain. Neural networks can learn complex patterns from data. Neural networks have been successfully used in areas such as natural language processing. or Deep Learning is a type of machine learning that uses neural networks with multiple layers. Each layer consists of multiple nodes that can perform diverse tasks. This allows deep learning models to learn more complex patterns from data. Deep learning has been used to achieve significant results in a wide range of tasks, including image recognition, speech recognition, and machine translation. It is particularly useful for No specific requirements. The course is for any individual who want to build a career in AI and data science or improve their knowledge. or What is AI? AI is a field of computer science that studies how to create machines that can process information, make decisions, and perform specific tasks. or The History of modern AI. The field of artificial intelligence (AI) has a long and rich history, dating back to the early days of computing. However, the field as we know it today was founded in 1956 at a conference at Dartmouth College in New Hampshire. This conference brought together the leading researchers in AI at the time, including Alan Turing, John McCarthy, and Marvin Minsky. The conference is credited with helping to define the field of AI and to set the agenda for future research. or Artificial Intelligence “AI” is a complex field that needs the ability of people from diverse disciplines to work together. As an example, manufacturing autonomous vehicles like self-driving cars requires the work of people from different fields, such as AI Researchers, Automotive Engineers, and Computer Vision Researchers. AI Researchers develop algorithms that enable self-driving cars to perceive their surroundings, make decisions, and control their movements. Automotive Engineers develop the hardware and software systems that are needed to implement these algorithms, and Computer Vision Researchers develop new techniques for enabling self-driving cars to see and understand the world. or What is Machine Learning? Machine Learning is a type of Artificial Intelligence (AI) that allows computers to learn from data without explicit programming. In other words, machine learning algorithms can recognize patterns and make predictions based on data, without getting a command. This enables computers to learn new tasks and improve their performance over time without human intervention. or Where is Machine Learning used? Machine learning is in use by a wide range of applications, including email filtering, Social Media Personalization, Image Recognition, Speech Recognition, fraud detection, Text prediction, Product recommendation, medical diagnosis, Healthcare Personalization, Traffic Prediction. or Neural networks are a type of machine learning algorithm that is inspired by the structure and function of the human brain. Neural networks can learn complex patterns from data. Neural networks have been successfully used in areas such as natural language processing. or Deep Learning is a type of machine learning that uses neural networks with multiple layers. Each layer consists of multiple nodes that can perform diverse tasks. This allows deep learning models to learn more complex patterns from data. Deep learning has been used to achieve significant results in a wide range of tasks, including image recognition, speech recognition, and machine translation.

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Summary

Title: AI Essentials: Introduction to Artificial Intelligence

Price: $19.99

Average Rating: 4.2

Number of Lectures: 20

Number of Quizzes: 1

Number of Published Lectures: 20

Number of Published Quizzes: 1

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: €24.99

Quality Status: approved

Status: Live

What You Will Learn

• AI, it's Modern History and current Implementations
• Machine Learning
• Neural Networks and Deep Learning
• The relationship between Machine Learning, Neural Networks and Deep Learning
• The theory of Artificial General Intelligence (AGI)
• Intelligent agents
• Natural Language Processing (NLP)
• Computer Vision
• AI Ethics
• AI In Robotics
• Search Algorithms
• Knowledge Representation and Reasoning (KRR)
• Explain-ability and Transparency in AI (XAI)
• Generative Artificial Intelligence (GenAI)
• Large Language Models (LLMs)
• AI and IT
• AI for Good

Who Should Attend

• No specific requirements. The course is for any individual who want to build a career in AI and data science or improve their knowledge.
• What is AI? AI is a field of computer science that studies how to create machines that can process information, make decisions, and perform specific tasks.
• The History of modern AI. The field of artificial intelligence (AI) has a long and rich history, dating back to the early days of computing. However, the field as we know it today was founded in 1956 at a conference at Dartmouth College in New Hampshire. This conference brought together the leading researchers in AI at the time, including Alan Turing, John McCarthy, and Marvin Minsky. The conference is credited with helping to define the field of AI and to set the agenda for future research.
• Artificial Intelligence “AI” is a complex field that needs the ability of people from diverse disciplines to work together. As an example, manufacturing autonomous vehicles like self-driving cars requires the work of people from different fields, such as AI Researchers, Automotive Engineers, and Computer Vision Researchers. AI Researchers develop algorithms that enable self-driving cars to perceive their surroundings, make decisions, and control their movements. Automotive Engineers develop the hardware and software systems that are needed to implement these algorithms, and Computer Vision Researchers develop new techniques for enabling self-driving cars to see and understand the world.
• What is Machine Learning? Machine Learning is a type of Artificial Intelligence (AI) that allows computers to learn from data without explicit programming. In other words, machine learning algorithms can recognize patterns and make predictions based on data, without getting a command. This enables computers to learn new tasks and improve their performance over time without human intervention.
• Where is Machine Learning used? Machine learning is in use by a wide range of applications, including email filtering, Social Media Personalization, Image Recognition, Speech Recognition, fraud detection, Text prediction, Product recommendation, medical diagnosis, Healthcare Personalization, Traffic Prediction.
• Neural networks are a type of machine learning algorithm that is inspired by the structure and function of the human brain. Neural networks can learn complex patterns from data. Neural networks have been successfully used in areas such as natural language processing.
• Deep Learning is a type of machine learning that uses neural networks with multiple layers. Each layer consists of multiple nodes that can perform diverse tasks. This allows deep learning models to learn more complex patterns from data. Deep learning has been used to achieve significant results in a wide range of tasks, including image recognition, speech recognition, and machine translation.

Target Audiences

• No specific requirements. The course is for any individual who want to build a career in AI and data science or improve their knowledge.
• What is AI? AI is a field of computer science that studies how to create machines that can process information, make decisions, and perform specific tasks.
• The History of modern AI. The field of artificial intelligence (AI) has a long and rich history, dating back to the early days of computing. However, the field as we know it today was founded in 1956 at a conference at Dartmouth College in New Hampshire. This conference brought together the leading researchers in AI at the time, including Alan Turing, John McCarthy, and Marvin Minsky. The conference is credited with helping to define the field of AI and to set the agenda for future research.
• Artificial Intelligence “AI” is a complex field that needs the ability of people from diverse disciplines to work together. As an example, manufacturing autonomous vehicles like self-driving cars requires the work of people from different fields, such as AI Researchers, Automotive Engineers, and Computer Vision Researchers. AI Researchers develop algorithms that enable self-driving cars to perceive their surroundings, make decisions, and control their movements. Automotive Engineers develop the hardware and software systems that are needed to implement these algorithms, and Computer Vision Researchers develop new techniques for enabling self-driving cars to see and understand the world.
• What is Machine Learning? Machine Learning is a type of Artificial Intelligence (AI) that allows computers to learn from data without explicit programming. In other words, machine learning algorithms can recognize patterns and make predictions based on data, without getting a command. This enables computers to learn new tasks and improve their performance over time without human intervention.
• Where is Machine Learning used? Machine learning is in use by a wide range of applications, including email filtering, Social Media Personalization, Image Recognition, Speech Recognition, fraud detection, Text prediction, Product recommendation, medical diagnosis, Healthcare Personalization, Traffic Prediction.
• Neural networks are a type of machine learning algorithm that is inspired by the structure and function of the human brain. Neural networks can learn complex patterns from data. Neural networks have been successfully used in areas such as natural language processing.
• Deep Learning is a type of machine learning that uses neural networks with multiple layers. Each layer consists of multiple nodes that can perform diverse tasks. This allows deep learning models to learn more complex patterns from data. Deep learning has been used to achieve significant results in a wide range of tasks, including image recognition, speech recognition, and machine translation.