You can also install and use Python from the command line, and you can use an alternative Python development environment such as Visual Studio Code with the Python Extension. The version of Python on the client computer must match the version of Python on the server, and packages you install must be compliant with the version of Python you have. For information on which version of Python is included with each SQL Server version, see Python and R versions. To verify the version of Python on a particular SQL Server instance, use the following T-SQL command.

In this course for beginners, you will get started with Data Science and SQL Server Machine Learning Services. You will learn the basics of Data Science, as well as, how you can start implementing Data Science projects in SQL Server with Python, via its Machine Learning built-in feature. Data Science, Big Data, Machine Learning and Artificial Intelligence, are the areas of technology that have been significantly evolved over the last few years. These technologies, are already heavily used by many organizations, in order to efficiently solve complex problems. Among other, they are used for predicting patterns based on large data sets and thus transform raw data into meaningful knowledge.

In a previous article, we have discussed about what Machine Learning is and saw some of its applications. Today, we continue this series of articles, dedicated to Data Science, Machine Learning and Artificial Intelligence (AI), by discussing what SQL Server Machine Learning Services are, and how you can use them, for efficiently implementing high-quality Data Science projects in SQL Server. SQL Server Machine Learning Services, were originally released with SQL Server 2016, known as "R Services", with support for the R language. Later on, with the release of SQL Server 2017, one of its most significant features, was the enhanced support for Machine Learning which provided support for both R and Python programming languages. In this release of SQL Server, "R Services" were renamed to "Machine Learning Services".

Did you know that you can execute R and Python code remotely in SQL Server from Jupyter Notebooks or any IDE? Machine Learning Services in SQL Server eliminates the need to move data around. Instead of transferring large and sensitive data over the network or losing accuracy on ML training with sample csv files, you can have your R/Python code execute within your database. You can work in Jupyter Notebooks, RStudio, PyCharm, VSCode, Visual Studio, wherever you want, and then send function execution to SQL Server bringing intelligence to where your data lives. This tutorial will show you an example of how you can send your python code from Juptyter notebooks to execute within SQL Server.