Python Full Course for Beginners

The course begins with an overview of Python, highlighting its popularity and versatility in areas like web development, data science, and automation. It outlines the topics covered, including data types, variables, functions, and modular programming.

Python is presented as easy to learn and set up, yet powerful due to its ecosystem of libraries and modules. The video explores use cases such as web development, data science, machine learning, data collection, and automation, emphasizing its flexibility and multi-purpose nature.

This sections provides instructions for installing Python locally and downloading the PyCharm code editor. It details the importance of adding Python to the system path on Windows and differentiating between Python 2 and 3 on macOS. It also introduces both community and professional version of Pycharm.

The course covers fundamental Python syntax, including printing output and understanding the execution environment. It introduces key data types like strings, integers, and floats, along with string concatenation methods.

This segment demonstrates basic math operations in Python and the use of variables to store repeating values, which improves code readability and maintainability. It simplifies a calculation and explains more in deep about programming, such as modularizing the code.

The lesson explains functions for reusability and how to define them with input parameters. Variable scope (global vs. local) and how functions are defined and utilized, with emphasis on modularizing the code.

This section introduces accepting user input with the `input()` function, assigning it to variables, and the need for validation. It covers validating numeric input and using `if-else` statements for decision making.

The video explains if-else conditional statements with comparison operators. The importance of validating external number input (user input) for cases where numbers can be negative, zero or text using if, elif, and else statements.

This part introduces error handling to prevent program crashes due to invalid user input. And explains more in deep how try, except blocks prevents issues with external values being assigned into different variables.

Explains While and For loops for repetitive tasks, demonstrating While loops that use 'True' or booleans and explaining an easier approach how to stop an external iteration using While loops (by assigning a stop variable).

The lesson dives into constructing lists, changing values, data types within, calling functions, using external and user based lists and other things that happen over the lists.

The presenter talks about data structures like comments, where is explained that we can assign comments to functions and external data. Also presents code and data structure styling (more white lines etc to make the code more readable).

Explains sets versus code structure and how a set looks like. The course presents differences like how it's constructed, how does the data look like and how it can be extracted / compared versus code and functions (data structures/ styling etc).

Explains in deep modules functions like where and how to see them and make use of the external components. Explains a comparison of an already created external packages versus a standard module internal code based on functions etc.

The last demonstration of the course relates to how a file excel, JSON or otherwise can be constructed inside a module. Then that file would be extracted and data would be managed into a third party app based on external access.

Is defined a method to call specific code from any module. This can also explain how to declare or use an existing code to perform actions with an external class. Then the teacher goes on and explains more in details a data structure object related.

This last project explains how to import credentials from a third party outside module (Gitlab) that will return output like key files of code. This will also include how to authorize the external class.