Explore

Building Modern Python Applications on AWS

Approx. 24 hours to complete

Save Course

Go to Course

Course Summary

Learn how to build modern Python applications on AWS with this course. From serverless computing to containerization, you'll explore the latest technologies and best practices for building scalable and efficient applications in the cloud.

Key Learning Points

Discover the advantages of serverless computing and how to use AWS Lambda to create functions
Learn about containerization with Docker and Kubernetes, and how to deploy your applications with Amazon EKS
Explore the latest trends in machine learning and AI, and how to use AWS services like SageMaker and Rekognition to build intelligent applications

Learning Outcomes

Create scalable and efficient Python applications on AWS
Deploy applications using serverless computing and containerization
Build intelligent applications using machine learning and AI

Prerequisites or good to have knowledge before taking this course

Basic knowledge of Python programming
Familiarity with AWS services such as EC2 and S3

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced

Similar Courses

AWS Certified Developer - Associate
AWS Certified Solutions Architect - Associate

Related Education Paths

Notable People in This Field

CTO, Amazon.com
VP Cloud Architecture Strategy, Amazon Web Services

Related Books

Description

In modern cloud native application development, it’s oftentimes the goal to build out serverless architectures that are scalable, are highly available, and are fully managed. This means less operational overhead for you and your business, and more focusing on the applications and business specific projects that differentiate you in your marketplace. In this course, we will be covering how to build a modern, greenfield serverless backend on AWS.

Building brand new applications on AWS is a different task than lifting and shifting existing applications into AWS. When you have an existing application that you need to move to AWS, you might first look to using Amazon EC2 as your virtual machines, or maybe you might look into using docker containers and container hosting services like Amazon Elastic Container Service or Amazon Elastic Kubernetes Service. Those are all great application hosting options, but in most cases, they still require you to have some kind of pulse on the underlying infrastructure hosting your application. ` Building Modern Python Applications on AWS will explore how to build an API driven application using Amazon API Gateway for serverless API hosting, AWS Lambda for serverless computing, and Amazon Cognito for serverless authentication. We will follow an API driven development process and first mock up what the API will look like. We will cover all the ins and outs of the service Amazon API Gateway, and as you’ll learn- it does a lot more than just hosting an API. Then we will add authentication to the API using Amazon Cognito. You’ll learn about how the authorization flow works with Cognito, and how to build it into your APIs. From there, we will add a Lambda backend that will be triggered by API Gateway. The lambda functions will be using the AWS SDKs to perform various data processing tasks. You’ll learn about the different configurations that exist for Lambda, and we will show you how to create and manage lambda functions. Some of the features of our API will require multiple lambda functions to execute in a specific order, like a workflow, and we will use AWS Step Functions to create a serverless workflow. Finally, we will talk about how to optimize your APIs at every layer using AWS features. Note: There are four versions of this class, "Building Modern Node.js Applications on AWS" for Node.js developers, Building Modern Java Applications on AWS" for Java developers, "Building Modern .NET Applications on AWS" for .NET developers, and this course, "Building Modern Python Applications on AWS" for Python developers. The courses do for a large part, overlap and in general, we recommend that you take the course that focuses on the SDK you plan to use to develop your AWS Cloud based applications. We expect that you have basic knowledge of AWS already. Some examples of concepts you should be familiar with are: you should know the basics of the AWS Global infrastructure, like what regions and availability zones are. You also should know the at a high-level AWS Identity and Access Management, or IAM, and how it is used to control access to AWS resources. You should also understand what an Amazon EC2 instance is, what Amazon S3 is, what a VPC is, as well as other basic AWS terminology.

Outline

Week 1
Introduction to Building Modern Applications
Meet the Instructors
Architecture for the Cloud
Introduction to AWS Cloud9
Introduction to AWS API Management Console CLI SDK
AWS CLI Intro
AWS SDK Exploration (Python)
Using Temporary Credentials in AWS Cloud9
Serverless Application Model
AWS Toolkit for PyCharm
Introduction to Lab 1
Pre-Course Survey
Course Welcome and Student Information
Discussion Forums
Labs Overview
Demo Code
Cloud9, AWS APIs, AWS CLI
Cloud9 Temporary Credentials, AWS SDK, AWS Toolkits, AWS SAM - Python
Lab 1 Discussion
Mid-Course Survey
Week 1 Discussion
Lab 1 Feedback
Week 1 Quiz

Week 2
Introduction to Week 2
API Driven Development
What is API Gateway?
Dragon API: API Gateway Terminology
Models and Mapping
Creating a GET API with Mock Integration
Dragon API: Using Mappings
DragonAPI: Using Models
Publish API
Using Postman to Create Requests
Lab 2 Introduction
Introduction to Authentication and API Gateway
API Gateway Access Controls
API Gateway Authentication and Authorization
Introduction to Amazon Cognito
Use Amazon Cognito to Sign In and Call API Gateway
Lab 3 Introduction
What is API Gateway Notes, API Driven Dev Notes
Models, Mappings, Request Validation Notes
API Gateway Stages, deployments, invoking, Postman
Lab 2 Discussion
Cognito Notes
Lab 3 Discussion
Week 2 Discussion
Week 2 Quiz

Week 3
Introduction to Week 3
Introduction to AWS Lambda
AWS Lambda Execution
AWS Lambda Permissions
Triggers, Push, Pull Model
Lambda Execution Context Reuse
Compliance with AWS Lambda
Asynchronous vs Synchronous Responses
Aliases and Versions
Creating an AWS Lambda Function - Python Part 1
Creating an AWS Lambda Function - Python Part 2
Creating and Debugging AWS Lambda Functions with AWS Toolkit for PyCharm
Lab 4 Introduction
Intro Lambda, Lambda execution, Lambda Permissions
Lambda Push/Pull Model, Async vs Sync, Compliance
Creating a Lambda function, versioning and aliases
Lab 4 Discussion
Week 3 Discussion
Week 3 Quiz

Week 4
Introduction to Week 4
Creating a Serverless Workflow
Introduction to Step Functions
Step Function State Types
AWS Step Function Service Integrations
API Gateway and Step Function Integration Demo
Run a Job and Wait for Callback Patterns
Step Function Activities
Standard vs Express Step Functions
Event Driven Architectures
Lab 5 Introduction
Step Functions Terminology, State Types
Step Function Integrations
Express vs Standard, Callback URL and Task Tokens
SQS, SNS, EventBridge
Lab 5 Discussion
Week 4 Discussion
Week 4 Quiz

Week 5
Introduction to Week 5
Introduction to Observability
Introduction to AWS X-Ray
X-Ray, API Gateway, and Lambda
Using X-Ray: Python
CloudWatch Logs Integration with API Gateway, Step Functions, and Lambda
How to Configure CloudWatch Logs in API Gateway, Step Functions and Lambda (Part 1)
How to Configure CloudWatch Logs in API Gateway, Step Functions and Lambda (Part 2)
How to Configure CloudWatch Logs in API Gateway, Step Functions and Lambda (Part 3)
X-Ray Terminology
Logging
Week 5 Discussion
Week 5 Quiz

Week 6
Introduction to Week 6
Introduction to Edge-Optimized Endpoints
API Gateway Response Caching
Lambda @ Edge
Lambda Performance
Lambda Layers
Lambda Best Practices
API Gateway Proxy for AWS APIs
API Gateway HTTP APIs
Lab 6 Introduction
Course Wrap Up
Edge Locations, Response Caching, Lambda @ Edge
Lambda Layers, Performance Tuning, Best Practices
API Gateway Proxy, HTTP APIs, API Gateway Takeaways
Lab 6 Discussion
Week 6 Discussion
Post-Course Survey
Week 6 Quiz
Final Assessment

Summary of User Reviews

Discover how to build modern Python applications on AWS with this comprehensive course offered by Coursera. Students have praised the course for its practicality, real-world examples, and hands-on approach. Overall, the course has received high ratings from users.

Key Aspect Users Liked About This Course

The course is praised for its practicality and hands-on approach.

Pros from User Reviews

Real-world examples help students apply the concepts they learn in class.
The course is designed to be practical and hands-on, giving students the opportunity to work on real applications.
The instructors are knowledgeable and provide clear explanations of the concepts covered in the course.
The course is well-structured and easy to follow, with each module building upon the previous one.
The course covers a wide range of topics, from AWS basics to advanced Python programming.

Cons from User Reviews

Some users have reported that the course moves too quickly, making it difficult to keep up.
The course assumes some prior knowledge of Python and AWS, which may be challenging for beginners.
The course can be time-consuming, especially for students who are new to programming.
Some users have reported technical difficulties with the course materials, such as broken links or outdated information.
The course does not cover all AWS services in depth, which may be a drawback for students looking for a more comprehensive overview.

Recommended for you

LEARNING PATH: Webpack: Web Development with Webpack

Boost your application's performance with Webpack Webpack is a module bundler for modern JavaScript applications.  The highlights of this Learning Path are:...

Save Course

Learning Path: Data Science With Apache Spark 2

Get started with Spark for large-scale distributed data processing and data science Sounds interesting? Let’s see how easy it is! We then develop a real-world Spark application....

Save Course

Distributed Tasks Demystified with Celery, SQS & Python

Conjure up your first Python scalable background worker This course teaches beginners to industry professionals the fundamental concepts of Distributed Programming in the context of python & Django....

Save Course

Apache Spark Streaming with Python and PySpark

Add Spark Streaming to your Data Science and Machine Learning Python Projects What is this course about?     What will you learn from this Apache Spark streaming cour?...

Save Course