Name: PCAP Certification – Python Theory Study Guide (Part 2)
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Created byManoloiu Ionut-Alexandru

Last updated 6/2025

English

What you'll learn

Understand core Object-Oriented Programming (OOP) principles in Python, including classes, inheritance, and polymorphism.
Learn how Python iterators, generators, and closures work and how to apply them in practice.
Use Python lambdas, map(), filter(), and comprehensions to write cleaner and more efficient code.
Read from and write to files in Python using proper file-handling techniques and context managers.

Course content

2 sections • 8 lectures • 1h 24m total length

OOP fundamentals16:49
In this lesson, we will explore the fundamentals of Object-Oriented Programming (OOP). We will cover:
Class Concepts: Learn about the basic ideas and notions of OOP, including classes, objects, properties, methods, encapsulation, inheritance, superclass, and subclass.
By the end of this lesson, you will be able to:
Grasp the fundamental concepts of OOP.
Navigate and understand class structures.
Python OOP properties12:32
In this lesson, we will explore Python's Object-Oriented Programming (OOP) properties. We will cover:
Instance vs. Class Variables: Learn the difference between instance variables (specific to an object) and class variables (shared among all instances of a class), and how to declare and initialize them.
The __dict__ Property: Understand the __dict__ property for both objects and classes, which stores their attributes.
Private Components: Discover how to define private components in instances and classes, and understand the concept of name mangling.
Name Mangling: Learn about name mangling and how it helps in creating private variables.
Introspection: Use introspection to examine the properties of objects and classes, including the hasattr() function.
Class Properties: Explore class properties such as __name__, __module__, and __bases__.
By the end of this lesson, you will be able to:
Differentiate between instance and class variables.
Use the __dict__ property to access attributes.
Define and manage private components using name mangling.
Perform introspection to examine class and object properties.
Python Methods10:30
In this lesson, we will explore Python methods. We will cover:
Declaring and Using Methods: Learn how to declare methods within a class and how to use them effectively.
The self Parameter: Understand the role of the self parameter in methods and how it allows access to instance variables and other methods within the class.
Method Types: Explore different types of methods, including instance methods, class methods, and static methods, and understand their use cases.
By the end of this lesson, you will be able to:
Declare and use methods within a class.
Utilize the self parameter to access and modify instance variables.
Differentiate between instance methods, class methods, and static methods, and know when to use each type.
Python inheritance12:07
In this lesson, we will explore Python inheritance. We will cover:
Basic Inheritance: Learn how to create a parent class and a child class that inherits methods and properties from the parent class.
The super() Function: Understand how to use the super() function to call methods from the parent class.
Method Overriding: Discover how to override methods in the child class to provide specific implementations.
Multiple Inheritance: Explore how to create a class that inherits from multiple parent classes and understand the method resolution order.
By the end of this lesson, you will be able to:
Create and use parent and child classes.
Utilize the super() function to enhance code reuse.
Override methods to customize behavior in child classes.
Implement multiple inheritance and understand its complexities.

Python iterators and closures9:24
In this lesson, we will explore Python iterators and closures. We will cover:
Python Iterators: Learn how to create and use iterators to traverse through all the elements of a collection, such as lists, tuples, and dictionaries. Understand the __iter__() and __next__() methods and how to implement custom iterators.
Python Closures: Discover how closures work in Python. Understand how nested functions can capture and carry some of the outer function's state even after the outer function has finished execution.
By the end of this lesson, you will be able to:
Create and use iterators to efficiently traverse collections.
Implement custom iterators using the __iter__() and __next__() methods.
Understand and use closures to maintain state in nested functions.
Python files handling9:38
In this lesson, we will explore Python file handling. We will cover:
Opening and Closing Files: Learn how to use the open() function to open files in different modes (read, write, append, etc.) and how to properly close files using the close() method.
Reading Files: Discover various methods to read files, including read(), readline(), and readlines().
Writing to Files: Understand how to write data to files using the write() and writelines() methods.
File Modes: Explore different file modes such as "r" (read), "w" (write), "a" (append), "b" (binary), and "t" (text).
Using with Statement: Learn how to use the with statement to handle files, which ensures that files are properly closed after their suite finishes, even if an exception is raised.
By the end of this lesson, you will be able to:
Open and close files in various modes.
Read from and write to files using different methods.
Understand and use different file modes.
Utilize the with statement for efficient file handling.
Python lambda functions6:34
In this lesson, we will explore Python lambda functions. We will cover:
Lambda Function Basics: Learn what lambda functions are and how they differ from regular functions. Understand the syntax: lambda arguments: expression.
Using Lambda Functions: Discover how to use lambda functions for short-term tasks and within other functions. See examples of lambda functions for operations like addition, multiplication, and more.
Applications of Lambda Functions: Explore practical applications of lambda functions, such as using them with built-in functions like map(), filter(), and reduce().
By the end of this lesson, you will be able to:
Define and use lambda functions in your Python code.
Apply lambda functions for various operations and within other functions.
Utilize lambda functions with built-in Python functions for efficient data processing.
Python list comprehensions6:30
In this lesson, we will explore Python list comprehensions. We will cover:
List Comprehension Basics: Learn the syntax and structure of list comprehensions
Creating Lists: Discover how to create new lists based on existing iterables using list comprehensions.
Conditions in List Comprehensions: Understand how to apply conditions to filter items in the list comprehension.
Nested List Comprehensions: Explore how to use nested list comprehensions to handle more complex scenarios.
By the end of this lesson, you will be able to:
Write and understand basic and advanced list comprehensions.
Create lists efficiently using list comprehensions.
Apply conditions to filter items within list comprehensions.
Utilize nested list comprehensions for complex data structures.

Requirements

Basic understanding of Python syntax and programming concepts (variables, loops, functions).
Completion of PCAP Theory Part 1 or equivalent beginner-level Python knowledge.
A computer with Python installed (version 3.x recommended).

Description

Welcome to PCAP Theory Part 2 — your next essential step in mastering Python programming and confidently preparing for the PCAP certification exam! This course is thoughtfully designed to build upon foundational Python knowledge and guide you through some of the most important intermediate concepts that every Python developer should know.

In this course, you will dive deep into Object-Oriented Programming (OOP) principles, learning how to create robust, reusable, and organized code using classes, inheritance, encapsulation, and polymorphism. Understanding these core OOP concepts will not only help you write cleaner code but will also prepare you for real-world programming challenges and the PCAP exam questions.

We’ll also explore the powerful concepts of iterators, generators, and closures in Python — tools that enable efficient looping, lazy evaluation, and advanced function design. These are key to writing elegant and memory-efficient Python programs, and mastering them will set you apart as a proficient Python developer.

The course includes an in-depth look at lambda functions and Python’s functional programming capabilities like map(), filter(), and comprehensions. You’ll learn how to write concise and expressive code using these techniques, which are widely used in both industry and coding interviews.

Additionally, you will gain practical skills in file handling and manipulation — including how to open, read, write, and safely close files using context managers. This knowledge is fundamental for tasks involving data persistence, logging, and working with external data formats like CSV or text files.

This course is ideal for Python learners who have already grasped the basics and are eager to advance their skills. Whether you’re preparing for the PCAP certification exam or aiming to deepen your understanding of Python’s intermediate features, this course will provide you with clear explanations, real-world examples, and the theoretical knowledge you need to succeed.

Join now and continue your Python learning journey with confidence!

Who this course is for:

Python learners who have mastered the basics and want to deepen their understanding of OOP and advanced concepts.
Students preparing for the PCAP certification looking for theory-focused study materials.
Developers seeking to improve their Python skills with practical knowledge of iterators, closures, and file handling.
Anyone interested in writing more efficient, Pythonic code through lambdas and comprehensions.

What you'll learn

Explore related topics

Course content

Python OOP4 lectures • 52min

PCAP Miscellaneous4 lectures • 32min

Requirements

Description

Who this course is for: