What You Will Learn?
- Fundamentals of multithreading in Python
- How to implement message passing communication between processes to build parallel applications
- How to build a distributed social media data ingestor
- How to implement distributed tasks with Python & Django
- How to scale on the cloud with AWS Simple Queue Service (SQS)
This course on distributed computing will help both beginners, and the professionals in the industry to grasp the core concepts of distributed programming when it comes to Django & Python.
Distributed Computing for Beginners and Onwards
In this course, you will learn how to build applications which reduce latency and increase throughput. In the first part of this course, you will dive deep, which will help you build a strong foundation on how to work with asynchronous parallel tasks by using Python celery - a distributed task queue framework, as well as multithreading in Python. As it comes to scaling parallel tasks on the cloud, we will explore AWS SQS.
This fundamental knowledge will help you build a scalable Python solution for any Python project you can think of.
When you complete this course, you will know how to use popular distributed programming frameworks for Django and Python. That's how you will discover the world of distributed programming with Python and the easiness of being able to build distributed components into your Django and Python projects.
Four Reasons Take This Course
Python is a universal programming language, you can do nearly everything with it. When you know distributed computing, you will be able to do so much more. Here are four reasons to take this course.
First, if you want to be a Django web application developer or a Python developer, you must learn how to build apps that can process long running tasks or jobs in a non blocking way, for example running high computational functions or sending a mass email.
Second, this course will build up your skills in distribute programming and give you the tools you will need to scale your apps.
Third, in this course, you will learn about projects you can implement in the real world with the sole emphasis on allowing the apps to have asynchronous components and become distributed.
Fourth, while taking this course, you will have online access to the instructor, and you will receive individual answers to your questions which you posted on forums.
The Uses of Distributed Computing
It is a field of computer science which studies distributed systems - systems whose components are located on different networked computers.
Take a large task and break it down into smaller parts and have an entire bank of computers working on the problem instead of a single computer, and you have distributed computing on your hands.
This way you can complete the project much faster since you are using the processing power of all the computers in the bank. In other words, you can work on a task with one computer for a million years, or you can use a million computers to complete the task in a year.
Enroll in this course and learn how to build distributed Python apps. These skills will let you advance in career, enhance your knowledge and become the building blocks of going even further. And this process does not have to be dull, in this course you'll see that learning is involving and fun!
- Basic Python
- Basic programming fundamentals