Python: Beyond Intermediate

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Beginner

In this section, you'll dive into the basics of Python, familiarize yourself with your workspace, tackle simple math operations, and display your results.

Here, you'll learn how to store items like numbers and text in computer memory, recalling them by name. You'll also get a taste of text manipulation in Python.

Here, you'll delve into the boolean data type and discover its role in creating programs that respond to specific conditions.

Continuing with data types, this section will teach you how to group varied attributes within a single variable using lists, tuples, and the dictionaries.

In this part, you'll master the art of writing loops in Python – essential constructs for iterating over lists, tuples, dictionaries, and even future dataframes.

To wrap up our introductory course, you'll explore some built-in functions and then embark on creating your very own!

We will consider what a function in Python and some basic techniques used to create functions is: what are the arguments of the function, what is the return value of the function, what is the body of the function, and how to use the function in the code.

Learn how to define functions in Python using positional and optional arguments. Master the flexibility of creating functions that adapt to different input scenarios.

Learn to work with arbitrary arguments and keyword arguments in Python to handle variable numbers of inputs. Understand how arbitrary arguments manage flexible positional inputs and how keyword arguments organize named arguments into a dictionary for efficient function design.

The return value of a function is the direct result of the execution of the function, which we can use in the program. There are several types of function return values - we will consider the most commonly used.

Explore the power of recursion and lambda functions in Python. Understand how recursion allows a function to call itself for solving complex problems, and how lambda functions provide a concise way to define anonymous functions for simple tasks.

You'll find this topic enjoyable, and you'll learn how to pack and unpack values in a single assignment.

Explore the power of Python's function arguments, *args, **kwargs, and learn how to effectively use functions as arguments.

Discover the higher-order functions and how functions can be passed as arguments to other functions in programming.

What is variable scope, and how did we manage without it before? This topic is essential for understanding the following subjects: Closures and Decorators. I assure you that this topic will be both enjoyable and practical. You will gain knowledge about local, nonlocal, and global variables.

This section provides an in-depth exploration of Python decorators, a powerful feature that allows for the modification and enhancement of function behavior. Participants will learn how to write their own decorators, understand built-in decorators, and apply decorators in practical scenarios.

This is a hands-on course that will help you understand the basics of object-oriented programming in Python. You will learn how to create classes, work with objects, use inheritance, and extend the capabilities of your programs.

If you find yourself frustrated with import statements, the difference between modules and libraries, or managing your Python project structure, this section is your key to clarity.

Want to debug your code effectively and understand the power of leveraging various errors? This section demystifies error handling in Python, showcasing why it’s crucial for developers to master these skills for robust applications.

Eager to automate file operations in your projects? This section delves into the essentials of file handling in Python, equipping you with the tools to read, write, and manage files efficiently for smoother, more powerful applications.

You will learn the ins and outs of testing with Pytest and the fundamentals of Test-Driven Development (TDD). This section guides you through creating robust tests that enhance your code's reliability and streamline your development process.

Master automation testing with Unittest. Learn how to cover various test cases effectively using setup, teardown, and mocking.

In Python, iterators and generators are key concepts that enable efficient and memory-friendly data processing. While iterators follow a specific protocol for accessing data sequentially, generators simplify iteration by producing values on demand with the yield keyword. This section explores these concepts and their practical applications, helping you master memory-efficient programming.