Python Advanced

The Advanced Python Course is designed for individuals with a basic understanding of Python who wish to deepen their knowledge and expertise in the language. The course provides a comprehensive dive into Python’s advanced features, focusing on both theoretical concepts and practical applications to help participants build proficiency in writing efficient, maintainable, and scalable Python code.

This course is ideal for software developers, data scientists, system administrators, and anyone who already has a working knowledge of Python but wants to advance their skills. If you’ve mastered the fundamentals and are ready to take on more complex tasks and challenges, this course will provide the necessary tools and knowledge to elevate your programming capabilities.

The course is divided into several modules, each focusing on different advanced topics. It covers a range of concepts, from in-depth data types to complex object-oriented programming (OOP) techniques. Participants will gain both theoretical knowledge and hands-on experience through practical sessions, applying learned concepts to real-world scenarios.

1. Introduction to Python The course begins with an overview of Python’s design philosophy, its properties, and its goals as a programming language. This section emphasizes why Python is widely used in fields like web development, machine learning, automation, and data science. Additionally, participants will be introduced to essential tools and Integrated Development Environments (IDEs), such as PyCharm, Visual Studio Code, and Jupyter Notebooks, to streamline their development workflow.
2. Data Types Understanding Python’s internal representation of data types is crucial for writing optimized code. This module covers both scalar data types (such as int, bool, float, and str) and container types (such as list, tuple, dict, and set). Participants will learn how these types are managed under the hood and how to use them effectively.
3. Control Flow Control flow statements are critical for managing the execution of code. This module delves into branching statements (if, elif, else), loops (for, while, break, continue, and else), and introduces Python's newer pattern matching feature. Exception handling will also be covered to ensure participants can handle errors gracefully in their programs. Practical exercises will help reinforce the usage of these control flow mechanisms.
4. Functions Functions in Python are powerful and flexible. This module explores function declaration, parameter passing, and how functions are treated as first-class objects, allowing them to be passed around and used within other functions. The section will also introduce advanced function concepts such as lambda functions, closures, and decorators, giving participants the ability to write more efficient and reusable code. The hands-on practice will enable participants to experiment with these concepts in various coding scenarios.
5. File Handling Managing files is an essential part of many Python applications. In this module, participants will learn to handle file input/output (IO) operations efficiently, use context managers (with statement) for safe file handling, and work with common serialization formats like JSON and Pickle. This section emphasizes real-world applications, with practical exercises on handling different types of files and data formats.
6. Modules and Packages Organizing and structuring code across multiple files and projects is key to scalability. This section covers importing and managing Python modules, creating packages, and working with virtual environments to manage dependencies. By the end of this module, participants will be able to structure large projects efficiently and use virtual environments to isolate project dependencies, improving project maintainability and collaboration.
7. Object-Oriented Programming (OOP) This extensive module provides a deep dive into Python’s object-oriented programming features. Participants will explore class creation, encapsulation, inheritance, and polymorphism. More advanced topics, such as multiple inheritance, Method Resolution Order (MRO), and the use of super(), will be discussed. Magic methods, operator overloading, and collection encapsulation will allow participants to create intuitive and powerful Python classes. This section also covers the iterator and generator protocols, which are essential for managing sequences of data efficiently. Furthermore, participants will learn about the descriptor protocol and metaclasses, giving them the ability to customize and extend Python’s object model in advanced ways. This module includes extensive practical sessions, allowing participants to apply OOP principles in real-world coding scenarios.

By the end of the Advanced Python Course, participants will be able to:

• Write optimized, efficient Python code using advanced data structures and functions.
• Utilize Python’s control flow and exception handling mechanisms to manage program execution.
• Create and manage files, work with different data formats (like JSON and Pickle), and handle file IO effectively.
• Organize Python projects using modules and packages and manage project dependencies with virtual environments.
• Master object-oriented programming principles, including inheritance, polymorphism, and advanced class mechanisms.
• Implement complex features such as iterators, generators, and decorators to create more efficient and readable code.
• Understand and utilize Python’s advanced object model, including the descriptor protocol and metaclasses.

This course provides an in-depth look at advanced Python features, combining theoretical knowledge with practical applications. By the end of the course, participants will have gained the expertise needed to write robust, maintainable, and high-performance Python code. Whether you’re developing web applications, handling data science projects, or building automation scripts, this course will equip you with the skills to succeed at a higher level.

Learn advanced uses for Python.

• Recap basic features, OOP
• Learn advanced features – decorators, iterators, generators, MRO, metaclasses
• Learn how to use Python development tools

1. [Theory – 1h; practice – 0h] Introduction to Python

a. Language properties and goals

b. Main language use cases

c. IDE and tools

2. [Theory – 2h; practice – 0h] Data types

a. Data internal representation

b. Scalar data types: bool, int, float, str, ...

c. Container types: list, tuple, dict, set, ...

3. [Theory – 2h; practice – 2h] Control flow

a. Branching: if/elif/else, pattern matching

b. Loops: while, for, break, continue, else

c. Exception handling

4. [Theory – 4h; practice – 3h] Functions

a. Function declaration and argument passing

b. Function as a first-class object

c. Lambdas, closures

d. Decorators

5. [Theory – 2h; practice – 3h] Files

a. Files IO

b. Context managers

c. JSON, Pickle

6. [Theory – 2h; practice – 2h] Modules and packages

a. Importing modules

b. Packages

c. Virtual environments

7. [Theory – 12h; practice – 5h] Object-oriented programming

a. Class declaration

b. Encapsulation, Inheritance, polymorphism

c. Multiple inheritance, MRO, super()

d. Magic methods

e. Operator overloading

f. Collection encapsulation

g. Iterator protocol

h. Generators

i. Attribute access

j. Descriptor protocol

k. Meta classes