Developing your AI skills using SQL. If you want to ensure you aren't left behind by developments in AI and machine learning that it may pay to learn relevant skills that you can use to implement your own strategies. At least by understanding the tools used in AI and machine learning, you will be able to navigate these new horizons and make smarter decisions for your business. One of the key concepts to understand then is SQL. SQL stands for Structured Query Language and is a declarative language that is used to store and retrieve information from a database. If that sounds like gobbledygook, it basically provides a set of commands you can use to manipulate large datasets.

SQL is crucial for data science and machine learning. It takes a number of forms such as my SQL, SQL Server, and SQL Lite. Each uses a slightly different dialect to achieve the same thing interact with relational databases. relational databases consist of numerous tables like you see an Excel with columns and rows. So if you had a lot of visitors to your website, you might fill out their data across rows, such as name, age, contact details, etc. Pull out any given visitor, and it will bring their details up so that you're ready to call them and market to them.

SQL then allows you to do things like creating whole new tables or inserting new rows, columns or cells. You can do this with simple commands like CREATE TABLE and insert into to make a new database, you first need to use a command to make it and from there, you can then begin inserting tables like so. One of the most powerful commands is something called select, which allows you to retrieve information across one or more tables. For instance, you can use this to get the details of anyone over a certain age like so. group by is a command that lets you group results according to certain conditions. cursors let us move through sets of data and make changes.

While this all might seem quite simple, combined with huge amounts of data, these simple commands can yield fascinating results and be extremely useful. And informing future decisions. This is essential how machine learning works. And if you ever want to work as a data scientist to employ Big Data solutions or machine learning applications, this is what you will need to know.