Developing AI Applications with Python and Flask

In this module, you will explore the differences between Python libraries and frameworks and understand how frameworks like Flask simplify web application development. You will be introduced to Flask’s core features and learn how to set up and run basic Flask applications. The module covers key web development concepts such as defining routes, handling request and response objects, working with dynamic URLs, and managing errors using appropriate status codes. You will also learn about decorators in Flask and how they are used in application logic. Through hands-on labs, you will build RESTful APIs, implement GET and POST request handling, and incorporate error handling techniques. The module concludes with deploying your Flask application on the web and implementing additional features like CRUD operations, dynamic URL generation, and form handling to build fully functional web applications.

In this module, you will be introduced to Embeddable Watson AI libraries and apply them by building two AI-based applications. 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 improve your skills and proficiency. For both projects, you will implement unit testing, perform static code analysis, and incorporate error handling to ensure your applications are reliable and production ready.