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Implement Natural Language Understanding(NLU) with IBM Cloud, Django user authentication, set up CI/CD, create django models, views, and proxy services, create pages for all views, containerize with docker.

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kevinmbuicode/USA-Car-Dealership-with-IBM-Cloud

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Final IBM Project - Lite Account

  • The Lite account may need payment by the time you see this, but use this code. Note: It was approved by the time I submitted this. Now on to IBM text: The final project for this course has several steps that you must complete. To give you an overview of the whole project, all the high-level steps are listed below. The project is then divided into several smaller labs. You must complete all the labs to successfully complete the project.

Project Breakdown

Prework: Sign up for IBM Cloud account and create a Watson Natural language Understanding service

  1. Create an IBM cloud account if you don't have one already.
  2. Create an instance of the Natural Language Understanding (NLU) service.

Create a repository with a project then build and deploy the project

  1. Create static pages to finish the user stories
  2. Deploy the application on IBM Cloud

Add user management to the application

  1. Implement user management using the Django user authentication system.
  2. Set up continuous integration and delivery

Implement backend services

  1. Create cloud functions to manage dealers and reviews
  2. Create Django models and views to manage car model and car make
  3. Create Django proxy services and views to integrate dealers, reviews, and cars together

Add dynamic pages with Django templates

  1. Create a page that shows all the dealers
  2. Create a page that show reviews for a selected dealer
  3. Create a page that let's the end user add a review for a selected dealer

Containerize your application (docker)

  1. Add deployment artifacts to your application
  2. Deploy your application

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Implement Natural Language Understanding(NLU) with IBM Cloud, Django user authentication, set up CI/CD, create django models, views, and proxy services, create pages for all views, containerize with docker.

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