0.3.2 Course overview of AI in Practice: Applying AI

Course subject(s) Module 0: Getting started: AI in Practice: Applying AI

Goal of the course

After having learned what the implications of AI can be for your organization or for our society in the Preparing for AI course, 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 the 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 the Municipality of Amsterdam, Thirona, The Dutch National Police, Elsevier, ING, and Ahold Delhaize.

AI in Practice – Applying AI gives learners the ammunition to understand the practical aspects required for the implementation of a variety of AI applications in your organization.

Learning Objectives

After taking this course learners will be able to:

    1. Describe the benefits and challenges of implementing AI in organizations, in terms of context, organizational background and problems, research approach and results.
    2. Identify the conditions and requirements of implementing AI in terms of improvement strategies for organizations in industry, academia and education.
    3. Understand the implementation aspects of AI and their significance for a learners own organization.
    4. Write a plan of approach on how AI can be applied in a learners own organization.

Course Overview

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

    1. Reinforcement Learning for Real life (AI for FinTech Research) and as a bonus track, Self-Learning Forecasting in Retail (AIRLab – Amsterdam).
    2. Diagnostic Image Analysis for COVID-19 (Thira Lab).
    3. Thematic Track: AI Strategy and Implementation Aspects of AI (Vrije Universiteit Amsterdam, Dutch National Police, Elsevier, Delft University of Technology).
    4. Agent Architecture of the Intake (Police Lab AI – Utrecht).
    5. AI for Society (Civic AI Lab).

In each module of this course, one or more topics are explained from the perspective of a selection of guest lecturers from ICAI labs, working in industry or academia.

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AI in Practice: Applying for AI by TU Delft OpenCourseWare is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on a work at https://online-learning.tudelft.nl/courses/ai-in-practice-applying-ai//
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