Python is a dynamic, strongly typed, object-oriented, multipurpose scripting language for the web. In this hands-on course students first learn the basics of writing and running Python scripts and then move into more advanced topics like file operations, regular expressions, working with binary data, and how to use Python modules. Topics include basic Python language components, the IDLE environment, control flow constructs, strings, I/O, collections, classes, modules, and regular expressions.

In this hands-on, case study-based course, students will learn Python for data science, including Python Functions, String, List, Set and Dictionary, and Packages through guided lectures, labs, and get hands-on experience tackling interesting data problems from start to finish.

In this Python training course, students already familiar with Python programming will learn advanced Python techniques such as Jupyter Notebook, the Collections module, mapping and filtering, lamba functions, advanced sorting, working with regular expressions in Python, working with databases, CSV files, JSON and XM, writing object-oriented code, testing and debugging and learning about Unicode and text encoding. This advanced Python course is taught using Python 3, however, differences between Python 2 and Python 3 are noted.