Artificial Intelligence Basics

Name: Artificial Intelligence Basics
Author: Chintan Thakkar

Learn the foundations of AI theory and components, testing, uses in robotics and the Internet of Things, and the ethical and practical challenges of AI applications

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Welcome to KnowledgeCity's course What is Artificial Intelligence? In these lessons, you'll explore the difference between natural and artificial intelligence or AI, learn about weak AI versus strong AI and examine thinking machines and the objectives of AI research. Artificial intelligence is a computer program that allows us to create intelligent systems that make choices similar to the human brain. The system is designed to perform the following learn new concepts, produce output based on learning, simulate the human brain's behavior, perform logical thinking and generate a conclusion, build new models and learn from existing models and understand natural language, perform transformation and generate an outcome. An artificial intelligence program often builds knowledge incrementally. For example, let's say you want to predict turbine failure. A machine learning program analyzes data patterns and learns from existing choices made by human operators to then build a knowledge base. It will then analyze incoming data and use the knowledge base to make decisions. This system generates the output with accuracy and reduces the number of human hours needed. However, the system needs to be tested with many different variations before using it on the actual production data. Turbine failure isn't a one time problem. It's a recurring problem that can easily be solved using an artificial intelligence program. An artificial intelligence program can be designed to learn from images and videos. For example, a program can collect the type of videos users watch by learning user preferences. The program can then start showing recommended videos to the end users, which may increase overall traffic on the web application. The programs are often designed to understand human language and behavior. Let's say you leave your home every day at 11am. Your security system keeps track of your entry and exit, display alerts, and makes choices to inform the users about enabling the security system. Artificial intelligence systems can also be designed to make instant decisions. We can use the example of an autopilot use case in electronic vehicles. The system collects data about road conditions and traffic patterns and can support autopilot mode with the ability to make faster decisions. The system supports learning, problem solving, reasoning and overall perception. The artificial intelligence systems can help us improve machine learning tasks and generate a more accurate out output. You can think about comparing artificial intelligence to natural intelligence. Natural intelligence is associated with humans and how humans come up with an answer to a complex problem. For example, in the time it may take a doctor to make a diagnosis of a patient, an artificial intelligence can perform many diagnoses with a much shorter time and it can easily be configured to scale if needed during a higher load. In another example, what if a bank wants to send out credit Card offers to 1,000 customers? They've hired 15 agents for reviewing credit scores and sending the offers, it will take them a day or more to complete the task. If they create an artificial intelligence program, it can do the same tasks in much less time depending on the infrastructure. You can easily scale up and optimize the algorithm if you need results within a few seconds. Here are some concerns related to natural intelligence. It can be hard to transfer expertise from one user to another. It can be difficult to explain logical reasoning behind a decision. It can be difficult to document everything regarding natural intelligence and it can often cause work to be duplicated. Here are some main advantages of an artificial intelligence system. It allows us to reduce the human hours needed for a task. It can increase overall efficiency. It supports testing a program under certain real life situations. It reduces overall errors it handles the automation of manual tasks. It allows us to replace humans with machines for risky situations such as space exploration. It can help us build the tools for future predictions and it can act as a growth engine for health related advancements.

Beginner Provider : Chintan Thakkar 4 chapters · 17 Lessons · 1h in Arabic, English

Course Description

In this course on Artificial Intelligence (AI) Basics, you’ll explore what AI is, how it’s changing the way people live and work, its current and potential real world applications, the key attributes of AI, and the ethical challenges it presents.

The first few lessons in this course will discuss the differences between “natural” and “artificial” intelligence as well as the strengths and limitations of AI. You’ll learn the primary objectives of AI research, how AI is improving human life, and the key components of AI. In the next lessons, you’ll discover AI theory and testing, along with the different types of AI agents with their terminology and different environmental properties, and you’ll learn about statistical and neural language modeling with artificial intelligence. Following these lessons, you’ll explore the two types of machine learning solutions, as well as AI and the use of robotics. You’ll understand unsupervised and supervised machine learning algorithms, the various branches of artificial intelligence, and the benefits of applying AI to data analytics. You’ll also gain knowledge of natural language processing, and how AI can help you design and build a robot that can be given commands but also complete repetitive tasks. Finally, in the last lessons of this course, you’ll see how deep learning in artificial intelligence is being used in smart cars and even for automated content creation. You’ll recognize how different applications and web services use AI, like chatbots and transcription programs. These lessons will also focus on the challenges with AI and the ethical considerations regarding AI and machine learning.

What You'll Learn

Distinguish between natural and artificial intelligence and understand the strengths and limitations of AI
Compare weak AI and strong AI and explore the objectives of AI research
Examine AI theory and testing, AI agents, and environmental properties
Explain statistical and neural language modeling and unsupervised and supervised machine learning algorithms
Explore how AI is applied in robotics, data analytics, deep learning, and the Internet of Things (IoT)
Recognize the ethical challenges and considerations surrounding AI and machine learning

Key Takeaways

Artificial intelligence differs from natural intelligence and has both strengths and limitations.
AI research has primary objectives aimed at improving human life, and AI can be categorized as weak AI or strong AI.
Machine learning includes supervised and unsupervised algorithms, and AI spans many branches such as natural language processing and robotics.
Deep learning in AI is used in applications such as smart cars and automated content creation, as well as in web services like chatbots and transcription programs.
AI presents ethical challenges and considerations that apply to both AI and machine learning.

Frequently Asked Questions

What does this course cover?

This course explores what AI is, how it is changing the way people live and work, its current and potential real-world applications, the key attributes of AI, and the ethical challenges it presents. It covers natural versus artificial intelligence, weak and strong AI, AI theory and testing, AI agents and environments, language modeling, machine learning, robotics, data analytics, deep learning, the Internet of Things, and ethical considerations.

Who is this course for?

This course is for learners who want to understand the basics of artificial intelligence, including its key components, objectives, applications, and ethical challenges.

What skills will I gain from this course?

You will gain knowledge in Applications of Artificial Intelligence, Artificial General Intelligence, Artificial Intelligence Systems, Artificial Intelligence, Artificial Intelligence Development, and Explainable AI (XAI).

What will I learn about machine learning in this course?

You will explore the two types of machine learning solutions and understand unsupervised and supervised machine learning algorithms, along with the various branches of artificial intelligence and the benefits of applying AI to data analytics.

Does this course address the ethics of AI?

Yes. The course discusses the challenges with AI and the ethical considerations regarding AI and machine learning, and learning about ethical challenges with AI is one of its stated objectives.