CS50-Python certification

CS50’s Introduction to Programming with Python
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Github repository
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Here you can check the Github repository used trough the course.

Certificate
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Here you can see my certificate of the course.

Week 0: Functions, Variables
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This week covers fundamental programming concepts including functions, data types, and debugging techniques, providing a foundational understanding for writing and troubleshooting code.

Key concepts

Concept	Details
`Functions`	A block of code that performs a specific task.
`Bugs and Debugging`	Mistakes in the code and how to fix them.
`Data Types`	The type of data that a variable can store.
`Named Parameters`	Parameters that are passed by name.
`String Methods`	Methods that can be used with strings.
`Integers and Operators`	Operators that can be used with integers.
`Type Conversion`	Converting one data type to another.

Week 1: Conditionals
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This week discusses control flow elements like conditionals and logical operators, which are essential for making decisions in code and controlling how it executes.

Key concepts

Concept	Details
`Comparison Operators`	Operators that compare two values.
`if`	A way to run code conditionally.
`elif`	A way to run code conditionally if the first condition is false.
`else`	A way to run code if all other conditions are false.
`or`	A way to combine conditions.
`not equal`	A way to check if two values are not equal.
`and`	A way to combine conditions.
`chains`	A way to combine multiple conditions.
`modulo`	A way to get the remainder of a division.
`boolean`	A way to represent true or false values.
`pythonic expressions`	A way to write code in a more concise way.
`match`	A way to match a value to a pattern.

Week 2: Loops
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This week focuses on loops in programming, detailing how to iterate over data structures using for and while loops, and discussing concepts such as nested loops and list iteration.

Key concepts

Concept	Details
`Loops`	The ability of doing something multiple times.
`while`	A way to repeat a block of code while a condition is true.
`for`	A way to repeat a block of code a number of times.
`Validating input`	A way to ensure that the input is correct.
`Iteration with Lists`	A way to iterate over a list.
`len`	A way to get the length of a list.
`Dictionaries`	A way to store key-value pairs.
`List of Dictionaries`	A way to store a list of dictionaries.
`Nested Loops`	A way to have a loop inside another loop.

Week 3: Exceptions
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This week focuses on error management in Python, detailing different types of exceptions and methods to handle them, ensuring robust and error-free code execution.

Key concepts

Concept	Details
`Exceptions`	A way to handle errors in the code.
`Syntax Error`	A mistake in the code that the Python interpreter cannot execute.
`ValueError`	An error that happens when you try to convert a string to a number, but the string is not a number.
`try, except`	A way to handle exceptions.
`NameError`	An error that happens when you try to use a variable that is not defined.
`else`	A way to run code if the try block does not raise an exception.
`Reprompting, break`	A way to reprompt the user if the input is not valid.
`get_int`	A way to create a function to get an integer from the user.
`pass`	A way to do nothing.
`function arguments`	A way to pass arguments to a function.
`raise`	A way to raise an exception.

Week 4: Libraries
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This week introduces the concept of libraries and modules in Python, explaining how to import and use them, along with mentioning popular libraries for statistical analysis and file handling.

Key concepts

Concept	Details
`Libraries`	A piece of code that someone else wrote that you can use in your code.
`Modules`	A library that has one or more functions built into it.
`import`	To use a module, you have to import it.
`from`	The keyword to import a specific function from a module.
`statistics`	A built-in module in Python that has a set of functions to calculate statistics.
`Command-line Arguments, sys`	The sys module provides access to some variables used or maintained by the interpreter and to functions that interact strongly with the interpreter.
`Packages, PyPI, pip`	Package: A collection of modules. PyPI: Python Package Index, a repository of software for Python. pip: a package installer for Python.
`Custom Libraries`	Create your own library.

Week 5: Unit Tests
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This week highlights the importance of testing in software development, discussing unit tests and the use of frameworks like pytest to ensure code quality and reliability.

Key concepts

Concept	Details
`Unit Tests`	A way to test the code you wrote.
`assert`	A way to test the code you wrote.
`AssertionError`	A way to handle an AssertionError.
`pytest`	A testing framework that makes it easy to write small tests.
`Side Effects and Testing`	A way to test the code you wrote.
`Collection of Tests`	A way to group tests together.

Week 6: File I/O
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This week covers file input/output operations, explaining how to read and write data, manage file formats like CSV, and manipulate data structures such as lists and dictionaries.

Key concepts

Concept	Details
`File I/O`	A way to read and write data to and from files.
`lists`	Data is stored in a list, but the moment the program is closed, the data is lost.
`open`	Used to open a file.
`with`	Used to open a file and automatically close it when the block is done.
`Reading from a file`	Use the `read` method to read the entire file, or `readline` to read one line at a time.
`sorted`	Used to sort a list.
`Comma-Separated Values (CSV)`	A file format used to store tabular data.
`sort keys`	Used to sort a list of dictionaries by a key.
`Lambda Functions`	A way to create small anonymous functions.
`CSV Library`	A library that can be used to read and write CSV files.
`Images, PIL Library`	A library that can be used to read and write images.

Week 7: Regular Expressions
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This week explores regular expressions as powerful tools for string matching and validation, detailing how to use them effectively within Python programs.

Key concepts

Concept	Details
`Regular Expressions`	A pattern that we can use to match strings.
`Validation with Regular Expressions`	A way to validate strings using regular expressions.
`re Library`	A library that allows us to define a pattern to match strings.
`Regular Expressions Patterns`	A set of symbols that can be used to match strings.

Week 8: Object-Oriented Programming
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This week outlines the principles of OOP, including classes, objects, and inheritance, emphasizing how these concepts facilitate code organization and reuse.

Key concepts

Concept	Details
`Object-Oriented Programming (OOP)`	A programming paradigm that uses “objects” to design applications and computer programs.
`Tuples`	A collection of objects that are ordered and immutable.
`Dictionaries`	A collection of key-value pairs that is more powerful than a list.
`Classes and Objects`	A class is a blueprint or a mold for creating objects.
`Instance Methods`	Functions defined inside a class used to perform operations on objects of that class.
`Types and Classes`	A type is a category of values, and a class is a blueprint for creating objects.
`Class methods`	Methods that are bound to the class and not the object of the class.
`Static methods`	Methods that are bound to the class and not the object of the class.
`Inheritance`	A way to create a new class that is based on an existing class.
`Operator Overloading`	A way to define how an operator behaves when used with a class.

Week 9: Et Cetera
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This week presents advanced programming features like sets, global variables, type hints, and comprehensions, enhancing Python’s functionality and readability while promoting best practices.

Key concepts

Concept	Details
`set`	A collection of unique elements; an unordered collection of items.
`global`	Used to declare that a variable inside the function is global (outside the function).
`constants`	A type of variable whose value cannot be changed.
`Type Hints, mypy`	A static type checker for Python.
`Docstrings`	A string that appears right after the definition of a function, class, or module.
`argparse`	A module in the Python standard library that allows you to parse command-line arguments.
`unpacking`	A way to assign the elements of an iterable to multiple variables.
`map`	A function that applies a given function to each item of an iterable (list, tuple, etc.).
`List Comprehensions`	A way to create lists in Python.
`filter`	A function that filters elements of an iterable based on a given function.
`Dictionary Comprehensions`	A way to create dictionaries in Python.
`enumerate`	A function that adds a counter to an iterable.
`Generators, Iterators`	A way to create iterators in Python.