Developing AI Applications with Python and Flask

In this module, you will start with the basic difference between web applications and APIs. Next, you will learn about the application development lifecycle, from gathering requirements to maintaining the project. You will also get familiar with the best practices for coding as documented in the Python Enhancement Proposal (PEP8) style guide. You will learn about static code analysis, which is used to ensure that the code you write adheres to the coding rules. Next, you will learn how to create and run unit tests. Finally, you will learn how to create, verify, and run Python packages.

In this module, you will be introduced to the definitions of and key differences between Python libraries and frameworks for application development. You will also learn about Flask, a Python-based micro framework used for web deployment of applications. The module will also introduce development and deployment concepts, including routes, request and response objects, error handling, and decorators. After building an API with Flask, you will also learn to deploy web apps using Flask.

In this module, you will be introduced to Embeddable Watson AI libraries. You will also have the opportunity to build two AI-based apps. The practice project will provide you with a challenge to apply your programming skills and incorporate the IBM Watson libraries to build a text-based Sentiment Analysis tool. You will be provided guidance through each step of the project. The final project, Emotion Detection based on the text input, will help you get your skills and proficiency assessed by your peers. For both projects, you will perform unit testing, static code analysis, and incorporate error handling.