Python is an interpreted high-level general-purpose programming language. Unlike HTML, CSS, and JavaScript, which are primarily used for web development, Python is versatile and can be used in various fields, including software development, data science, and back-end development. In this course, you'll explore the core aspects of Python, and by the end, you'll be crafting your own functions!

This course is for you if you are new to SQL, you want to quickly learn how to get the most out of SQL and you want to learn how to use SQL in your own application development.

Pandas is an extremely user-friendly library for data analysis. It's also designed to handle large datasets, using data structures like DataFrame and Series. This makes it an invaluable tool for Data Science. In this guide, you'll get acquainted with a range of statistical functions, including how to find correlations, modes, medians, and maximum and minimum values within a dataset. You'll also learn how to handle missing values and manipulate specific values, as well as how to remove them.

This course is for you if you already have a basic knowledge of SQL, but want to learn more advanced things in order to create more powerful queries. In the course, you will get acquainted with grouping of data, filtering of grouped data. Also learn to work with several tables from the database at the same time, combining them. Learn about different types of table joins, learn how to use them in practice.

NumPy is one of the basic packages for scientific computing in Python. The 'NumPy in a Nutshell' course will introduce you to such a powerful tool as NumPy, which is convenient for working with arrays of different sizes. After completing this course, you will be able to easily work with matrices, using various functions. In addition, during the course, you will learn basic methods for working with arrays that simplify code writing.

Navigating the intricacies of Business Analysis is a transformative journey that unveils the dynamic intersection of strategy, technology, and organizational objectives. Delve into the heart of this discipline, where professionals craft solutions, facilitate change and bridge the gap between business needs and IT capabilities.

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

SQL, or Structured Query Language, is essential for data management, particularly in databases where information is stored, organized, and analyzed within tables. Meanwhile, modern Integrated Development Environments (IDEs) are indispensable for software development, providing coding and debugging tools, task automation, and streamlined interfaces to boost productivity and reliability. These tools work in tandem to expedite high-quality software development.

Data is everywhere around us and making sense of it is extremely important. Visulization helps us deal with data by finding certain patterns and insights in it. We will develop a solid foundation of data visulization using Python and its libraries, such as matplotlib and seaborn, to get as much information from data as possible in a neat and concise way. Without further ado, let's dive in!

Linear Regression is a crucial concept in predictive analytics. It is widely used by data scientists, data analytics, and statisticians as it is easy to build and interpret but powerful enough for many tasks.

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