100+ Ćwiczeń - Zaawansowane programowanie w języku Python

seem to be a comprehensive list of skills and knowledge areas related to Python programming and other computational techniques that you have encountered or are interested in. Python indeed is a versatile language that can be used for a wide range of applications, from web development (using frameworks like Django or Flask) and data analysis (with libraries such as pandas and NumPy) to machine learning and artificial intelligence (leveraging TensorFlow or PyTorch).

Here's a brief overview of the skills you've mentioned:

1. Database Management with SQLite: SQLite is a lightweight, file-based database system that doesn't require a separate server process. Python can interact with SQLite databases using libraries like sqlite3.

2. Levenshtein Distance (Edit Distance): This is a string metric for measuring the difference between two sequences. It's useful in various applications, including text processing and autocorrect features.

3. Caesar Cipher: A simple encryption technique where letters are shifted a certain number of places down or up the alphabet.

4. Morse Code: A method used to encode text into a series of dots and dashes to be transmitted with signal systems.

5. Monte Carlo Method: A statistical simulation technique used to model complex systems and evaluate unpredictable random events, based on repeated random sampling.

6. Bitwise Operations (AND, OR, XOR): These are binary operations performed on bits, which can be very useful for efficient data processing.

7. Functional Programming: A programming paradigm where functions are treated as first-class citizens—that is, they can be assigned to variables, passed as arguments to other functions, and returned as the result of other functions.

8. Object-Oriented Programming (Inheritance): This allows a class to extend another class and inherit its methods, which can help in creating more organized and manageable code.

9. Numerical Computing (Matrix, Vector Operations): Python's NumPy library provides support for large, multi-dimensional arrays and matrices.

10. Stack and Queue Implementation: Data structures that operate using a principle of "last in, first out" (LIFO) for stacks and "first in, first out" (FIFO) for queues.

11. HTML Validation: Using Python to validate the correctness of HTML documents or nested parentheses, brackets, and braces.

12. Financial Analysis (Moving Averages, Minima/Maxima): These techniques are used to smooth data or to find local minima and maxima, which can be useful in analyzing time series data in finance.

13. Kolejka (Queue) Implementation: As mentioned earlier, a queue is a collection of entities that are maintained in a given order and can be modified by the insertion of entities at one end and their removal from another end, which is exactly the opposite operation as that on a stack.

Your skill set indicates a strong foundation in computing and programming with Python. The combination of these skills allows for a wide range of applications in various fields such as finance, data science, artificial intelligence, cryptography, and more. Whether you're looking to solve complex problems, analyze large datasets, or develop new algorithms, Python is an excellent choice as a programming language due to its versatility and the extensive ecosystem of libraries and frameworks available.