Data Science is a relatively new field in the tech world. There are organizations in nearly every industry going digital and with the transition comes huge amounts of data. Data is extremely useful for business. Data scientists and analysts are more in-demand than they’ve ever been before.

Data is an important part of web applications, mobile apps, and, of course, data science. Data for these applications is stored in a database system. Developers and data scientists need to be able to access that data, manipulate it, extract it, and create it. That’s where SQL comes in! 

SQL is operating the databases behind the social networks we use, the apps on our computers, and even our online banking transactions. It’s useful for almost any industry and any application that needs to store or access data.

Machine learning uses data to teach a machine how to make an informed decision based on patterns in datasets. Python can be used for every stage of machine learning from data extraction to the development of complex algorithms. Python’s massive selection of libraries makes machine learning easier than ever. 

Python is the most beginner-friendly programming language for machine learning. It offers an easy to read syntax and a strong support network. Machine learning is complex, but Python offers libraries to help developers create faster and more securely.

Data Science is used by businesses and researchers alike to find meaningful insights into the numbers. IT, e-commerce, healthcare, news organizations, political campaigns, and more are using data science to maximize their work. In 2018, 66% of data scientists reported using Python every day. 

Python is a beginner-friendly programming language with an easy to read syntax and simple testing mechanisms. It’s loved by developers around the world who make up a strong support network for this open-source tool.