This course explores the Python Data Science Stack - the set of tools and libraries used in Python for data science applications. The course uses real-world datasets and examples to teach you how to apply various tools to process, analyse, and visualise your own data science projects. Once you have completed this course, you will have a solid foundational knowledge of the principles of applying Python to a variety of data science applications.
The Python programming language has become a major player in the world of Data Science and Analytics. This course introduces Pythonâs most important tools and libraries for doing Data Science; they are known in the community as Python's Data Science Stack. This is a practical course where the viewer will learn through real-world examples how to use the most popular tools for doing Data Science and Analytics with Python. Style and Approach. This course introduces the viewer to the main libraries of Python's Data Science stack. Taking an applied approach, it provides many examples using real-world datasets to show how to effectively use Pythonâs tools to process, visualize and analyze data. It contains all you need to start analyzing data with Python and provides the foundation for more advanced topics like Predictive Analytics.
Data analysts or data scientists interested in learning Python’s tools for doing Data Science. Business Analysts and Business Intelligence experts who would like to learn how to use Python for doing their data own analysis tasks will also find this tutorial very helpful. Software engineers and developers interested in Python’s capabilities for analyzing data gain a lot from this course. A basic (beginner’s level) familiarity with Python language is assumed.