Python Deep Dive

Python Deep Dive

Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis. Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn’t specialized for any specific problems. This versatility, along with its beginner-friendliness, has made it one of the most-used programming languages today. Python is commonly used for developing websites and software, task automation, data analysis, and data visualization.

COURSES OVERVIEW

Python Deep Dive

Module 1: Advanced Data Structures

Sets, frozensets, and advanced set operations
Collections module (deque, defaultdict, Counter)
Namedtuples and data classes
Custom data structures and their applications

Module 2: Functional Programming

Higher-order functions
Lambda functions
Closures and decorators
The functools module
Functional programming techniques

Module 3: Advanced Object-Oriented Programming

Multiple inheritance and method resolution order (MRO)
Abstract base classes (ABCs)
Mixins and composition
Operator overloading
Metaclasses and class creation

Module 4: Concurrency and Parallelism

Threading vs. multiprocessing
Python’s Global Interpreter Lock (GIL)
Thread synchronization (Locks, Semaphores)
Multiprocessing with the multiprocessing module
Asynchronous programming with asyncio

Module 5: Design Patterns

Creational, structural, and behavioral design patterns
Singleton, Factory, Observer, and others
Applying design patterns to real-world problems
Anti-patterns and their avoidance

Module 6: File Handling and Input/Output

Binary file I/O
Context managers and the with statement
Serialization (pickle, JSON, XML)
Working with streams and sockets

Module 7: Database Interaction

Connecting to databases using Python
Performing CRUD operations
Working with SQLite, MySQL, or PostgreSQL
Object-Relational Mapping (ORM) with SQLAlchemy

Module 8: Testing and Debugging

Unit testing with the unittest framework
Test-driven development (TDD)
Debugging techniques and tools
Profiling and optimizing Python code

Module 9: Web Development with Python

Introduction to web frameworks (Django, Flask)
Building RESTful APIs
Handling authentication and authorization
Deploying Python web applications

Module 10: Data Science and Machine Learning

Introduction to data science libraries (NumPy, pandas)
Data visualization with Matplotlib and Seaborn
Introduction to machine learning with scikit-learn
Real-world data analysis and modeling

Module 11: Final Project

Applying advanced Python concepts to a substantial project
Developing a Python application or solution
Presenting and showcasing the project

Module 12: Course Conclusion and Next Steps

Recap of advanced concepts and skills learned
Resources for further learning and specialization
Career opportunities in advanced Python programming

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