AI in Practice: Applying AI (edX)

AI innovative solutions, such as the use of machine learning, deep learning, computational argumentation, diagnostic image analysis, reinforcement learning, natural language processing, robotics and data analytics, can help organizations solve specific problems, drive efficiency and improve performance and decision-making.
After having learned what AI can do for your organization, this second part of our two-course program ‘AI in Practice’, will guide you in the practical aspects of applying AI in your own organization. You will examine typical applications of AI in use already and learn from their experience. These include challenges of implementation, lifecycle aspects, as well as the maintenance and management of AI applications.
To understand how current Artificial Intelligence applications can be successfully integrated in organizations, we look at different examples. For instance, how ING uses reinforcement learning for personalized dialog management with its customers or how Radboud UMC uses diagnostic image analysis to discover early stages of infectious diseases. The course presents a variety of case studies from actual situations in public organizations and private enterprises in the healthcare, financial, retail and telecommunications sectors. These include Radboud UMC, the Municipality of Amsterdam, ING, Ahold Delhaize and KPN.
‘AI in Practice – Applying AI’ gives you the ammunition to understand the practical aspects required for the implementation of a variety of AI applications in your organization.
This course has been developed by Delft University of Technology and the Innovation Center for Artificial Intelligence Academy (ICAI). ICAI is a national initiative involving industry, universities and government in the area of AI research and applications.
This course is part of the AI in Practice Professional Certificate.

What you'll learn
After taking this course you will be able to:

• Describe the benefits and challenges of implementing AI in organizations, in terms of context, organizational background, problems, research approach and results.
• Identify the conditions and requirements for the implementation of AI in terms of improvement strategies for organizations in industry, academia and education.
• Understand the implementation aspects of AI and their significance for your own organization.
• Write a plan for the application of AI in your own organization

Syllabus

The course is built from five main topics on AI in Practice:

1. Reinforcement Learning for Real life - the AI for FinTech Research (ING and Delft University of Technology) and a Bonus Track of the Self-Learning Forecasting in Retail - the AI for Retail Lab Amsterdam (Ahold Delhaize and University of Amsterdam).
2. Diagnostic Image Analysis for COVID-19 - the Thira Lab (Thirona and RadboudUMC).
3. Thematic Track on AI Strategy and Implementation Aspects of AI - a variety of labs (Vrije Universiteit Amsterdam, Dutch National Police, Elsevier and Delft University of Technology).
4. Agent Architecture of the Intake - the Police AI Lab Utrecht (University Utrecht and the Dutch National Police).
5. AI for Society - the Civic AI Lab (the Municipality of Amsterdam, University of Amsterdam and Vrije Universiteit Amsterdam).

In each module of this course each topic is explained from the perspective of a selection of guest lecturers from ICAI labs, working in industry or academia.
This course is designed for people who want to apply AI in their own practical situation. This applies to managers who want to know what AI can do for their companies, data analysts and consultants who want to understand how AI can be applied in their business processes, or students who want to understand how the results of AI research can be translated into practical applications.