Training: Python Fundamentals

• start the course
• describe the features of the Python programming language and how and where it is used
• describe the philosophy of Python
• recognize reasons to choose one version of Python over the other
• install Python 3 on Windows
• install Python 3 on Mac OS X and Linux
• evaluate the major IDEs available for Python
• use whitespace to lay out a Python program into functional code blocks
• recognize the Python REPL – read, evaluate, print loop
• create and execute a "Hello World" application with Python
• get and manipulate user input from the command line with Python
• create a module and import a module in Python
• use the int data type in Python and recognize its characteristics
• use the float data type in Python and recognize its characteristics
• perform basic math functions, such as addition, subtraction, multiplication and division, and use the Math module
• use the bool data type in Python and recognize its characteristics
• describe sequence types and use the str type in Python
• use the bytes type in Python
• use the bytearray type in Python
• use the list type in Python
• use the tuple type in Python
• use slicing on sequence types in Python
• use the range function and work with range objects in Python
• use the set type in Python and describe its characteristics
• use the dict type in Python and describe its properties
• construct a while loop in Python
• construct a for loop in Python
• use the if statement in Python to control program flow
• write a Python program to reverse user input

• start the course
• create and import a module at the Python REPL
• define a function in Python
• describe the difference in operation between Python scripts, programs and modules
• run a module as a script using the __name__ == __main__ syntax in Python
• create a main function that takes command line arguments in Python
• describe the relationship between classes and types in Python
• create a class definition and describe the structure in Python
• write a class initializer method in Python
• write and use class instance methods in Python
• write and use static methods in Python
• use inheritance and describe the semantics in Python
• describe class properties in Python
• describe how inheritance affects properties in Python
• write a class that implements operator overloading in Python
• write docstrings in Python
• write comments in Python
• describe best practice for documenting Python code as set out in PEP 8
• read text files in Python
• write data in Python
• write large files in Python
• read binary data in Python
• write binary data in Python
• write a Python class to represent a vector

• start the course
• create a list comprehension in Python
• create a nested comprehension in Python
• use the zip() function in a generator in Python
• create a set comprehension in Python
• create a dictionary comprehension in Python
• describe the function of iter(), next() and StopIteration() in Python iteration
• use the map() function in an iteration in Python
• use the filter() function in an iteration in Python
• use functools.reduce() to iterate over an iterable
• implement a custom iterable class in Python
• implement an iterable using consecutive integer indexing in Python
• implement an iterable using the extended iter() function
• create a simple generator in Python
• create a lazy generator in Python and understand its characteristics
• create a recursive generator in Python
• write a basic exception handler in Python to catch all exceptions
• write an exception handler in Python to catch a specific error, and recognize the reason why catching all errors is bad practice
• describe the inheritance hierarchy of exceptions in Python and how to catch multiple exception types using a base type
• raise an exception using a payload and retrieve a payload when handling an error
• create a custom exception class in Python
• access and manipulate traceback objects for an exception in Python
• use assertions in a Python program
• use implicit and explicit chaining of exceptions in Python
• create an iterable data type that handles exceptions in Python

• start the course
• describe the key features of the Django framework
• install and configure the Django framework
• create a Django project
• configure the Django web server
• create a sample Django app
• incorporate views and templates in an app
• use Django to include data in a Python web application
• utilize forms in a Python web application
• describe the key features of the TurboGears framework
• install and configure the TurboGears framework
• incorporate TurboGears templates into a Python web app
• incorporate TurboGears views into a Python web app
• create and use a controller in a Python web app
• describe rendering and how it is used in TurboGears
• use TurboGears to include data in a Python web application
• use RESTful URLs in TurboGears
• describe the key features of Flask
• create a basic Flask application
• incorporate a template into a Flask app
• work with web forms in a Flask project
• connect to and retrieve data using a Flask app
• use Django to create a view for a Python web application

Python is a high-level programming language that has code readability and simplicity as its primary design goals. Coupled with a few key APIs, it also becomes a very powerful data analysis tool. This course will cover basic data science fundamentals and apply them to Python.