Developing AI Applications with Python and Flask

Developing AI Applications with Python and Flask

This course is part of multiple programs.

Instructors: Abhishek Gagneja

What you'll learn

Describe the steps and processes involved in creating a Python application including the application development lifecycle
Create Python modules, run unit tests, and package applications while ensuring the PEP8 coding best practices
Explain the features of Flask and deploy applications on the web using the Flask framework
Create and deploy an AI-based application onto a web server using IBM Watson AI Libraries and Flask

Skills you'll gain

Software Testing

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 3 modules in this course

This mini course is intended to apply basic Python skills for developing Artificial Intelligence (AI) enabled applications. In this hands-on project you will assume the role of a developer and perform tasks including:

- Develop functions and application logic - Exchange data using Watson AI libraries - Write unit tests, and - Package the application for distribution. You will demonstrate your foundational Python skills by employing different techniques to develop web applications and AI powered solutions. After completing this course, you will have added another project to your portfolio and gained the confidence to begin developing AI enabled applications using Python and Flask, Watson AI libraries, build and run unit tests, and package the application for distribution out in the real world.

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.

What's included

7 videos3 readings2 assignments4 app items3 plugins

7 videosTotal 38 minutes

Introduction to the Course2 minutesPreview module
Application Development Lifecycle6 minutes
Introduction to Web Applications and APIs 4 minutes
Demo: Working with an IDE 5 minutes
Python Style Guide and Coding Practices 6 minutes
Unit Testing 6 minutes
Packaging 5 minutes

3 readingsTotal 10 minutes

Helpful Tips for Completing this Course 3 minutes
Prerequisites and Course Syllabus5 minutes
Module 1 Summary: Python Coding Practices and Packaging Concepts2 minutes

2 assignmentsTotal 40 minutes

Module 1 Practice Quiz: Python Coding Practices and Packaging Concepts10 minutes
Module 1 Graded Quiz: Python Coding Practices and Packaging Concepts30 minutes

4 app itemsTotal 105 minutes

Hands-on Lab: Getting Started with IDE 15 minutes
Hands-on Lab: Static Code Analysis30 minutes
Hands-on Lab: Practice Session and Assignment on Unit Testing30 minutes
Hands-on Lab: Practice Session and Assignment on Python Packaging30 minutes

3 pluginsTotal 25 minutes

Reading: Python with Flask for Large-Scale Projects5 minutes
Reading: Static Code Analysis Resources15 minutes
Module 1 Cheatsheet: Python Coding Practices and Packaging Concepts5 minutes

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.

What's included

7 videos1 reading2 assignments4 app items3 plugins

7 videosTotal 45 minutes

Python Libraries and Frameworks for Application Development3 minutesPreview module
Introduction to Flask 7 minutes
Flask - Basic Applications and Routes 7 minutes
Request and Response Objects – Using GET and POST Modes 8 minutes
Dynamic Routes 4 minutes
Error Handling5 minutes
Deploying Web Apps using Flask8 minutes

1 readingTotal 2 minutes

Module 2 Lesson Summary: Web App Deployment using Flask 2 minutes

2 assignmentsTotal 40 minutes

Module 2 Practice Quiz: Web App Deployment using Flask 10 minutes
Module 2 Graded Quiz: Web App Deployment using Flask 30 minutes

4 app itemsTotal 155 minutes

Hands-on Lab: Get Started with Flask Basics20 minutes
Hands-on Lab: Building an API with Flask: Route Creation, Error Handling, and HTTP Requests45 minutes
Hands-on Lab: Building and Deploying a Web App using Flask App30 minutes
Hands-on Lab: Exploring Additional Features Flask60 minutes

3 pluginsTotal 30 minutes

Reading: Decorators in Flask10 minutes
Reading: Additional Features in Flask15 minutes
Module 2 Cheatsheet: Web App Deployment using Flask5 minutes

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.