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The world is being transformed by artificial intelligence (AI). Many businesses and industries are implementing this technology to improve predictability, streamline processes, and stay ahead of the competition. But introducing AI software and practices isn’t always easy.

In this course, you will learn how to successfully integrate AI into any organization. You’ll learn how to determine whether your organization could fully benefit from AI, as well as the technical capabilities necessary for deployment. You’ll learn how to perform business analysis and present a case for implementation.

Further, you’ll learn project management best practices to help install AI successfully. You’ll use the Scrum framework to build and deploy AI and to maintain the system when in production to collect data and model scenarios.

AI Project Management: Deploying and Maintaining AI for Business

According to Jonathan Fernandes, the framework needed for the introduction of AI to an organization can be broken into four key stages:

1. Business understanding

2. Data collection and analysis

3. AI modeling and evaluation

4. Deployment and monitoring of the AI model in production

# Deliverables

Each of the four stages has corresponding deliverables that we can target to achieve in order to move toward our goal of implementing AI.

## Business understanding

In this stage, the goal is to obtain business case approval.

## Data collection and analysis

The goal in this stage is to explore and develop business use cases for the collection and analysis of data.


Learn about the four frameworks that most teams use to implement AI.

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The Implementation Framework