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

  • Sets, frozensets, and advanced set operations
  • Collections module (deque, defaultdict, Counter)
  • Namedtuples and data classes
  • Custom data structures and their applications
  • Higher-order functions
  • Lambda functions
  • Closures and decorators
  • The functools module
  • Functional programming techniques
  • Multiple inheritance and method resolution order (MRO)
  • Abstract base classes (ABCs)
  • Mixins and composition
  • Operator overloading
  • Metaclasses and class creation
  • Threading vs. multiprocessing
  • Python’s Global Interpreter Lock (GIL)
  • Thread synchronization (Locks, Semaphores)
  • Multiprocessing with the multiprocessing module
  • Asynchronous programming with asyncio
  • Creational, structural, and behavioral design patterns
  • Singleton, Factory, Observer, and others
  • Applying design patterns to real-world problems
  • Anti-patterns and their avoidance
  • Binary file I/O
  • Context managers and the with statement
  • Serialization (pickle, JSON, XML)
  • Working with streams and sockets
  • Connecting to databases using Python
  • Performing CRUD operations
  • Working with SQLite, MySQL, or PostgreSQL
  • Object-Relational Mapping (ORM) with SQLAlchemy
  • Unit testing with the unittest framework
  • Test-driven development (TDD)
  • Debugging techniques and tools
  • Profiling and optimizing Python code
  • Introduction to web frameworks (Django, Flask)
  • Building RESTful APIs
  • Handling authentication and authorization
  • Deploying Python web applications
  • 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
  • Applying advanced Python concepts to a substantial project
  • Developing a Python application or solution
  • Presenting and showcasing the project
  • Recap of advanced concepts and skills learned
  • Resources for further learning and specialization
  • Career opportunities in advanced Python programming

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