Advanced Python Programming: OOP, Decorators & Projects (Udemy.com)

Ready to move beyond Python basics and write more capable programs? This Advanced Python Programming course helps you develop practical skills in object-oriented programming, functional programming, decorators, generators, regular expressions, database operations and file handling.

If you can already write conditions, loops and functions but need guidance applying more advanced concepts, this course gives you a structured next step. You will explore how Python functions and classes work, process text and data, connect Python to MySQL, and read and write common file formats.

The course combines explanations, coding examples and practical activities. An optional Python refresher helps you revisit the foundations before moving into intermediate and advanced Python topics.

Develop Your Python Functional Programming Skills

Learn how to work with functions as reusable parts of a program. Explore pure functions, higher-order functions and lambda expressions, then apply map, filter and reduce to transform, select and combine values.

You will practice how to:

• Write functions that return predictable results for their inputs.

• Pass functions as arguments and return functions from other functions.

• Use lambda expressions for short operations.

• Transform collections with map.

• Select matching items with filter.

• Combine values using reduce.

These techniques help you understand functional programming in Python and recognize where it fits into everyday programming tasks.

Understand Python Decorators and Generators

Decorators and generators are important steps beyond basic Python functions.

Learn how Python decorators wrap a function to extend its behavior. Follow examples that show how a wrapper works and how additional behavior can be applied without rewriting the original function.

Explore Python generators, the yield statement and retrieving values with next(). Understand how generating values as needed differs from building a complete collection in advance.

These lessons help you read unfamiliar Python code more confidently and begin applying these patterns in your own programs.

Build Programs with Python Object-Oriented Programming

Move from individual functions into organizing related data and behavior with Python OOP.

Start with classes and objects, then work through attributes, instance methods, self and object initialization. Explore inheritance and polymorphism through examples that demonstrate how classes can share and extend behavior.

Topics include:

• Creating classes and objects.

• Working with attributes and methods.

• Using self to access instance data.

• Initializing objects.

• Understanding different inheritance structures.

• Using super to access inherited behavior.

• Applying polymorphism.

• Understanding public attributes, underscore conventions and private-name behavior.

This section develops your understanding of object-oriented programming in Python so you can follow class-based code and begin structuring your own applications.

Find and Process Text with Python Regular Expressions

Learn Python regular expressions, also called regex, to identify patterns and work with text.

Explore character classes, special sequences, word boundaries and pattern-matching operations. Use Python’s regular expression tools to search for matches, extract information, split text and replace matching content.

Practice using:

• findall to retrieve matching results.

• search to locate a matching pattern.

• split to divide text using a pattern.

• sub to replace matching text.

These skills provide a foundation for text processing tasks such as identifying relevant information, checking input patterns and cleaning text.

Connect Python to MySQL Databases

Learn Python database programming by working with MySQL and the PyMySQL library.

Begin with database concepts and connection setup, then create databases and tables from Python. Practice CRUD operations: creating, reading, updating and deleting records.

You will work with:

• Database connections and cursors.

• CREATE statements for databases and tables.

• INSERT queries to add records.

• SELECT queries to retrieve information.

• UPDATE and DELETE queries.

• Parameterized query examples.

• WHERE conditions and LIMIT clauses.

This section shows how Python programs can store information beyond a single program run and retrieve it when needed.

Handle CSV, JSON and Excel Files with Python

Learn practical Python file handling using Pandas to read and write commonly used data formats.

Work with CSV files, Excel workbooks and JSON data. Explore loading information into DataFrames, inspecting the loaded data and exporting results.

These lessons help you understand how Python exchanges information with spreadsheets, datasets and other applications. They also provide a useful starting point for later study in data analysis and automation.

Apply Concepts Through Practical Python Examples

Connect the programming concepts to small applications, including a resume keyword filter and a daily expense tracker.

Use these examples to explore how functions and data-processing operations contribute to a working program. Run the code, change the inputs and experiment with different conditions to strengthen your understanding.

For more effective practice, try each task yourself before reviewing the solution. Then modify the example to handle a different situation. Making these changes helps you move from recognizing code to writing it independently.

Understand How Advanced Python Skills Fit into Larger Applications

The course also discusses maintainable code, software design thinking and the role of Python in AI systems.

These conceptual lessons explain where the programming skills you are learning can be useful. They provide context for understanding larger applications and choosing what to study next.

Who Is This Course For?

This course is suitable for:

• Python learners who know the fundamentals and want to progress.

• Students looking for an approachable introduction to advanced Python concepts.

• Developers who want to strengthen their understanding of OOP, decorators and generators.

• Python users interested in regular expressions, MySQL and file processing.