
Master the basics of Python for data science and machine learning through hands-on coding and tutorials, gaining confidence to write Python programs and begin your data science journey.
Explore data science with Python by building and manipulating matrices with lists, mastering dictionaries, and importing modules and packages, then using standard library tools for math, statistics, and dates.
Explore Python namespaces and scopes, including built-in, global, local, and nonlocal levels, and see how variables behave across functions and modules.
Define Python classes, create objects, and access or modify class and instance members with dot notation, using constructors and destructors to manage lifecycles, and explore inheritance including multiple inheritance.
This is the second part of course on basics of Python. It starts with Matrix implementation using List. Then Tuples, Dictionary and Array data structures are discussed. Modules and Packages are explained. Few Standard library modules are also discussed. Then, object oriented programming concepts in Python are discussed which includes namespace, scope, class, class objects and class inheritence.