What you'll learn
Definition Artificial Intelligence, Overview of AI Development
Understanding Ai Components, Machine Learning, Neural Networks, Natural Language Processing, Computer Vision,
Setting Goals Identifying Resources Choosing the Right Platform
Developing Ai, Gather Data, Train the Model
Prepare for Deployment, Choose the Most Effective Infrastructure
Requirements
No programming needed
Description
AI is a rapidly growing field, and the ability to build an intelligent system is becoming increasingly important. AI is a broad topic, and there are many different approaches and techniques that can be used to create an AI system. This article will provide an introduction to the basics of AI and explain how to build an AI system.First, it is important to understand the different types of AI and the different techniques used to build them. AI can be divided into two main categories: supervised learning and unsupervised learning. Supervised learning involves training a system to recognize patterns in data, while unsupervised learning involves discovering patterns in data without a predetermined set of labels. In addition, there are other types of AI, such as reinforcement learning, which rightwards a system for performing tasks correctly.Once you have chosen a type of AI to build, it is important to determine what data you need. Data is the foundation of any AI system, so it is important to collect the right type of data. If you are building a supervised learning system, then you will need labeled data, while unsupervised learning systems require unlabeled data. It is also important to ensure that the data is of high quality and contains all the necessary information.Once you have the data, you need to choose the right algorithm for your AI system. Different algorithms are suitable for different types of data and tasks, so it is important to choose the right one. Popular algorithms include deep learning, decision trees, and support vector machines.After you have chosen the algorithm, you need to train the system. This involves feeding the data into the algorithm and adjusting the parameters so that the system can learn. Usually, this is done using a technique called back propagation, which involves gradually adjusting the parameters over time.Finally, you need to evaluate the AI system to ensure that it is performing correctly. This can be done by comparing the results of the system against a set of labeled data or by comparing it against a human expert. If the system is performing correctly, then you can deploy it and start using it in real-world applications.Building an AI system is no easy task, but with the right tools and techniques, it is possible to create an intelligent system. By understanding the basics and following the steps outlined above, you can begin to build your own AI system.
Overview
Section 1: Lectures
Lecture 1 Module 1
Lecture 2 Module 2
Lecture 3 Module 3
Lecture 4 Module 4
Lecture 5 Module 5
For everyone who want to learn Artificial Intelligence


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