You can learn artificial intelligence by taking an online course or enrolling in a data science camp. Many boot camps offer an introduction to machine learning. Machine learning is a tool that uses AI that involves exposing an algorithm to a large amount of data. It allows AI to learn faster.
The best way to get started with AI is to review the basics. You can start with basic math and then, preferably, get your hands dirty with a coding language. Using Python is always recommended because of its large, supportive community and the large number of packages and libraries that will help you along your journey. The data sets for your exploratory learning projects are available from many different sources.
In addition to public cloud providers, Kaggle is another popular source and also a good learning resource in general. Government data is also increasingly available in digital format. Data, gov, of the U.S. Federal Government.
In the US, it claims to have more than 300,000 data sets. State and local governments also publish data on all kinds of topics, from restaurant health ratings to dog names. It allows you to learn in person from renowned MIT professors and industrial experts, and you'll learn all the essential concepts and skills needed to develop efficient AI systems. It goes beyond the narrow scope of deep learning in neural networks, which has been so important to the advances achieved to date in reinforcement learning and supervised learning.
Artificial intelligence can be considered as a set of algorithms that have the capacity to generate results without us having to tell you how to do exactly the same thing. If it's minimal or rusty, but you still want to develop a deep understanding of the foundations of AI, you'll benefit from taking some courses in mathematics to start with. A basic brain science course, such as Introduction to Psychology from MIT, provides a useful context for the relationship between human intelligence and artificial intelligence. However, especially as you move beyond datasets and game applications, you have to start thinking seriously about the degree to which you want to be limited to a single provider.
In addition to these courses, there are free websites or blogs that you can take advantage of to learn AI at your own pace. If you want to learn AI to solve real-life problems, there are tons of libraries and toolkits that will help you with just about any problem. One of the main reasons why people don't jump straight into the field of Artificial Intelligence is because they don't know where to start. If you're really new to programming, Programming for All (How to Get Started with Python) by Charles Severance, from the University of Michigan, won't get you in the bottom of the pool like the MIT course does.
But the above should give you an idea of the general branches of study that are probably most important before delving into machine learning and AI itself. For professional education on the subject, learn about Stanford's artificial intelligence programs. Machine learning is rapidly becoming essential in many industries, as it drives everything from recommendation engines in the retail sector to pipeline safety in the oil and gas industry and patient diagnostics and privacy in the healthcare industry. If you ask a layman with a superficial knowledge of technology to explain Artificial Intelligence, he will undoubtedly relate it to robots.
