AI for Business

This course will have a business oriented approach and give an introduction to Artificial Intelligence and Machine learning, what types of problems are a good fit for machine learning and how to deal with the organisational challenges that come with AI/ML.

The course will also introduce tools to gain insight into the goals for successful AI and Machine learning initiatives and how to evaluate them. We will also discuss how a business should be organized in order to get out of the PoC way of thinking​ ​and ​get the highest value out of machine learning and other data driven initiatives.

How do you evaluate the feasibility of a machine learning project before you start? We will discuss topics such as:

• How does the machine learning project generate business value
• What are the limitations in terms of regulatory limitations, ethics, hardware, security and interpretability
• How will the solution affect the user
• How to handle organizational challenges
• Data requirements such as access to data, data sources, amount of data, amount of data preparation
• Architectural requirements: deployment needs, testing and monitoring, integration

Course Objectives:

In this course, you will learn to:

• Get an introduction to AI and Machine learning
• Learn how to Identify business opportunities using AI
• Gain knowledge about tools to evaluate the feasibility of a machine learning project 
• Learn how to setup an AI organization
• Learn how AI development differs from normal application development
• Get insights into data requirements
• Get insights into business requirements

Audience:

• Executives (CEO/CTO/CIO)
• Business developers
• IT architects
• Product owners
• Project managers

Prerequisites:

Open for everyone

Course outline:

• Introduction to AI and Machine learning
• Possibilities and limitations of machine learning projects
• Open discussion around value proposition
• AI requirements
• Goals for successful machine learning projects
• Evaluation of opportunities and exercises
• Open discussion around how to best organize a business when developing machine learning applications

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