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AI Applications with Python and Flask

This section covers the development of AI applications using Python and Flask. It includes an introduction to Flask, a lightweight web framework, and how to integrate AI models into web applications. The focus is on building interactive applications that leverage AI capabilities, such as natural language processing and machine learning.

In this section

  • Module-1
    This module covers the distinctions between web applications and APIs, the phases of the application development lifecycle, and the use of Flask for Python web development. It highlights code organization, PEP8 standards, static analysis, unit testing, and Python packaging fundamentals.
    • Introduction to using flask
      This document introduces Python with Flask, highlighting its simplicity extensibility, and suitability for both small and large-scale web applications. It covers key features, scaling considerations, and real-world usage.
    • Web Application
      This document outlines the phases of the application development lifecycle from requirements gathering to maintenance, and highlights best practices for organizing code in web applications.
    • Web Api
      This document explains the fundamentals of web applications and APIs, their differences, architectures, and how they enable communication between software components. It covers web app structure, API roles, and practical examples for modern development.
    • Style Guide
      This document outlines Python style guidelines and coding conventions including PEP-8, naming standards, and static code analysis. It explains how to write readable, maintainable code and ensure compliance using automated tools.
    • Unit Testing
      This document introduces unit testing in Python, covering the process, naming conventions, test structure, and result interpretation. It explains how to build, execute, and review unit tests for reliable code quality.
    • Packaging
      This document explains Python modules, packages, and libraries, and provides step-by-step guidance on creating, verifying, and using Python packages for code organization and reuse.
  • Module-2
    This module introduces the differences between Python libraries and frameworks, focusing on Flask for web development. It covers routing, request handling, error management, decorators, RESTful APIs, CRUD operations, and deployment of Flask applications.
    • Libraries and Framework
      This document explains the differences between Python libraries and frameworks, and introduces Flask as a web development framework. It covers core concepts, setup, and practical usage for building web applications.
    • Flask Features
      This document details the main features of the Flask web framework, its dependencies, installation, and key differences from Django. It covers Flask’s extensibility, built-in tools, and popular community extensions for web development.
    • Routes
      This document explains how to create and configure routes in Flask, return responses, manage application configuration, and structure Flask projects for maintainability. It covers decorators, JSON responses, environment variables and best practices for organizing code.
    • Response and Request Objects
      This document explains the Flask request and response objects, their attributes, and how to handle HTTP methods, headers, query parameters, and custom responses in Flask web applications.
    • Dynamic Routes
      This document explains how to use dynamic routes in Flask, including passing parameters in URLs, calling external APIs, and validating parameter types for RESTful endpoints.
    • Error Handling
      This document explains HTTP status codes, error handling in Flask, and how to return appropriate error responses from API endpoints, including application-level error handlers.
    • Deploying Flask App
      This document explains how to install Flask, create and deploy a Python web application, and use Flask's features for CRUD operations and template rendering.
  • Module-3
    This module introduces Embeddable Watson AI libraries through hands-on projects, including building sentiment analysis and emotion detection tools. It emphasizes unit testing, static analysis, and error handling for reliable, production-ready AI applications.
    • Module- 4
      • 08-ibm-fssd-python-flask-kanban

        Product Backlog

        Epic: Complete Python Flask Course

        • due: 2025-09-01
        • tags: [python, flask, fullstack]
        • workload: Extreme
        • defaultExpanded: true
        • steps:
          • Review all course modules
          • Identify key deliverables
          • Set up development environment
          • Plan project milestones
          • Finalize documentation
          • Module-1 completed
          • Module-2 completed
          • Module-3 completed
          1Main Objectives:
2- Master Python and Flask for web development
3- Complete all three modules
4- Build and document a mini web app project
5
6Success Criteria:
7- All modules completed
8- Mini project delivered
9- All assignments submitted

        Sprint Backlog

        In Progress

        Story: Module 1 - Flask Basics and Setup

        • due: 2025-08-01
        • tags: [module-1, python, flask]
        • priority: high
        • workload: Normal
        • steps:
          • Watch module videos
          • Complete readings
          • Add visuals using mermaid and excalidraw
          • Submit assignments
          • Take module quiz
          • Add your module MCQ, if applicable
          1As a learner, I want to complete Module 1 so that I can set up Flask and understand its basics.
2Acceptance Criteria:
3- All module tasks completed
4- Quiz passed
5- Assignments submitted

        Story: Module 2 - Building Flask APIs

        • due: 2025-08-08
        • tags: [module-2, python, flask]
        • priority: high
        • workload: Normal
        • steps:
          • Watch module videos
          • Complete readings
          • Add visuals using mermaid and excalidraw
          • Submit assignments
          • Take module quiz
          • Add your module MCQ, if applicable
          1As a learner, I want to complete Module 2 to build and test RESTful APIs with Flask.
2Acceptance Criteria:
3- All module tasks completed
4- Quiz passed
5- Assignments submitted

        Story: Module 3 - Flask Templates and Deployment

        • due: 2025-08-15
        • tags: [module-3, python, flask]
        • priority: high
        • workload: Normal
        • steps:
          • Watch module videos
          • Complete readings
          • Add visuals using mermaid and excalidraw
          • Submit assignments
          • Take module quiz
          • Add your module MCQ, if applicable
          1As a learner, I want to complete Module 3 to use templates and deploy a Flask web app.
2Acceptance Criteria:
3- All module tasks completed
4- Quiz passed
5- Assignments submitted

        Review/QA

        Done

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