Programme Outline

Programme Outline

Our goal is to create and deliver an Artificial Intelligence Master’s Degree Programmе the modules of which will cover various parts of the AI knowledge areas from the e-CF, ICT Ethics and EDISON frameworks.

Programme Outline

In our aim to create a Human-Centred AI Master’s programme, the HCAIM Consortium follows the definition of AI HLEG: “The human-centric approach to AI strives to ensure that human values are central to how AI systems are developed, deployed, used and monitored, by ensuring respect for fundamental rights.”

To answer the requirements of this definition, the programme covers the technical, ethical and practical elements of artificial intelligence.

We have designed our content around the three phases of the MLOps lifecycle – development, deployment and maintenance of machine learning models. The three phases of MLOps are each subdivided into several topics that cover the technical (AI/ML), ethical and practical elements of that part of the MLOps lifecycle: modelling (the exploration of the data and the design of the AI/ML models), deployment (taking AI/ML models into production and connecting to existing systems), and evaluation (maintenance of an AI/ML model in production).

We created three core modules in alignment with the above-mentioned ML-Ops phases: Modelling (Module A), Deployment (Module B), and Evaluation (Module C). We added a fourth module – (D) Graduation, to enable students to show that they can independently solve challenges proposed by the industry based on current needs and requirements related to human-centred artificial intelligence. To support the students herewith, the lesson plan Research in Practice runs parallel to the other Modules and guides the students from the start of the programme in their thesis process. This covers the core of the Human-centered AI master.

The structure of the programme is visualised in the table below.

Module A
Modelling

Foundations of AI

A topic that covers all of the essentials required to develop a product or deliver a service based on ethical AI technology.

AI Modelling

A practical topic on AI Modelling introducing industry-based approaches, tools, methods and more.

Fundamentals of Ethics

Requirements engineering, bias detection, mitigation, and data governance. Fundamentals of ethics and information theory.

Module B
Deployment

Advanced AI / Deep Learning

A topic that provides deeper insight into the fundamental workings of AI and Deep Learning.

Organisational AI

AI in action, system architectures, data collection, reinforcement learning and stream processing.

Trustworthy AI

An introduction to Explainable AI (xAI) and practical tools to ensure transparency, reproducibility, and interpretation of models.

Module C
Evaluation

Future AI / Learning

This is a genuine, evidence-based thematic session, built with curiosity to inform organisational innovation.

Socially Responsible AI

Introduction to continuous monitoring, accountability and responsibility of artificial intelligence, and more.

Compliance & Legality

Legal frameworks, compliance auditing and ethical auditing, accountability and responsibility of AI.

Module D
Graduation

Master Thesis Project

The HCAIM programme is built based on the project-based learning (PBL) principle, in which the project (making a professional product) is placed centrally in the student’s learning trajectory.

In the Master Thesis project students show that they can independently solve challenges proposed by industry based on current needs and requirements.

Using the green button below, you can access all the Learning Events that make up the Human-Centered Artificial Intelligence Master. All Learning Events, including their flanking study material, are available in English and can also be easily translated by yourself into any of the EU languages using the eTranslation tool of the European Union.

All the materials are available under a Creative Commons Attribution-NonCommercial-NoDerivates 4.0 license (CC BY-NC-ND 4.0)

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