Course: Python Fundamentals
duration: 25 hours |
Language: English (US) |
access duration: 90 days |
Details
In this Python training course you will learn the basics and philosophy of Python. You will also learn the advanced techniques of Python including development of different functions and classes and file handling. Finally you will learn about comprehensions, concise syntax for creating Iterable objects. The course also includes "iteration", "iterables' and exception handling.
Among subjects covered are float data tuple type, range of functions, REPL, docstrings, PEP 8, comprehension, iterable data type and far more.
Result
After completing this course you are familiair with the basic
and advanced features of Python.
Prerequisites
You are familiar with the basics of Python or another
programming language.
Target audience
Software Developer, Data analist
Content
Python Fundamentals
Python: The Basics
- 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
Python: Classes and Modules
- 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
Python: Iteration and Exceptions
- 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
Python: Web Application Development
- 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: web2py and Test-driven Development
Python: Data Science Fundamentals
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.
Course options
We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.
Optional practice exam (trial exam)
To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam.
Optional practice lab
To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediately. The lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience.
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Mobile ready | Yes |
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