To earn the MC4genKI micro-credential, you must complete the following modules:

• Compulsory Module 1: Foundations (Learning Unit 1)
  AI as a learning tool: how large language models work, prompting, and the critical use of generative AI in practice
   
• Elective Module 2: Practical Applications
  You choose three learning units according to your needs, interests, and prior knowledge:
  • For users (no prior knowledge required), e.g. generative AI for studying and learning, image editing, literature research, and academic writing
  • For developers (programming knowledge is an advantage), e.g. open reasoning models, RAG and AI applications
     
• Compulsory Module 3: Self-Reflection & Learning Journey (Learning Unit 3)
  You reflect on your learning process and continue to develop your individual learning pathway with generative AI.
   
• Final Workshop (Learning Unit 4)
  You complete an online self-assessment to evaluate your level of competence and take part in the final workshop. There, you present your learning outcomes. Upon successful completion of the full programme, you may earn the MC4GenKI Micro-Credential.

The programme workload comprises 60 hours (equivalent to 2 ECTS credits).

If you would like to earn 3 or 5 ECTS credits instead, e.g. for recognition as a General Elective Module (AW/AWPF) or a Subject-Specific Elective Module (FWPF), depending on the applicable examination regulations, please contact us at an early stage. In this case, attendance at additional workshops and the completion of further assessed work will be required.

Contact person: Thu Van Le Thi <thuvan.lethi@th-nuernberg.de>

Prerequisite: This workshop is open to students from all disciplines and requires no prior knowledge.

Date: Thu, 5 March 2026, 9:00 a.m.–5:00 p.m.
Format: On-campus workshop. The room will be announced after registration.
Module: Compulsory Module 1 of the MC4GenAI programme

Description:

In a world shaped by digital innovation, it is essential for students to understand the potential of LLM technologies such as ChatGPT. The workshop is designed from the perspective of users and offers deeper insight into the technical foundations of LLMs. It also examines ethical and social implications, fosters critical thinking, and provides participants with extensive opportunities to practise individually and in groups, as well as to discuss examples in the context of their own studies.

Learning content:

Part 1: The Technology Behind Language Models

• What is artificial intelligence?
• The history of AI and AI language models
• The ecological footprint of ChatGPT
• The architecture behind language models
• How do large language models learn?
• The possibilities, limitations, and risks of LLMs

Part 2: Effective Prompting and Use Cases for Study Contexts

In the context of generative AI, prompting refers to how users can formulate clear and precise instructions in order to obtain the desired outputs, retrieve information on specific topics, or receive support for learning activities.

• Tips and techniques for formulating effective prompts
• Analysis of examples and case studies of successful prompting strategies
• Practical exercises in creating prompts for different study-related scenarios
• Discussion of good practice in using AI as a learning tool

Part 3: Critical Use of Generative AI

• Key frameworks and guidelines
• Reflection on one’s own learning behaviour and the role of AI in learning
• Academic integrity
• Evaluating the quality of AI-generated output

Speakers: Yilmaz Duman, Thu Van Le Thi, Dr Barbara Meissner

Format: On-campus workshop

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “MC4GenKI”

Prerequisite: This workshop is open to students from all disciplines and requires no prior knowledge.

Important: This workshop is the first part of Learning Unit 2.1. If you would like to complete the full MC4GenKI programme, please make sure to also register for the second part of Learning Unit 2.1.

Date: Sat, 7 March 2026, 9:00 a.m.–4:00 p.m.
Format: Online workshop. The Zoom link will be provided after registration.
Module assignment: Elective Module 2 of the MC4GenAI programme

Description:

Since 2019, artificial intelligence has seen rapid advances in the creation and editing of texts and images. At present, these developments appear to be accelerating even further. This workshop offers a practice-oriented introduction to AI-supported image editing. You will become familiar with key tools such as Stable Diffusion and other AI-based image applications, gain an understanding of how they work, and explore typical use cases first-hand, including their limitations, risks, and likely future developments.

Learning content:

ChatGPT, Stable Diffusion & Co. for Image Editing

• Overview of AI image tools and their current relevance
• How image tools work and how images are generated
• Use cases and fields of application
• Practical exercises and guidance on using Stable Diffusion and other tools
• Possible limitations and risks of these tools
• Challenges and opportunities in professional contexts and higher education teaching
• Anticipated future developments

Speaker: Martin Türck

Format: Online workshop

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “MC4GenKI”

Prerequisite: This workshop is open to students from all disciplines and requires no prior knowledge.

Important: This workshop is the second part of Learning Unit 2.1. If you would like to complete the full MC4GenKI programme, please make sure to also register for the first part of Learning Unit 2.1.

Date: Wed, 11 March 2026, 9:30–11:00 a.m. (90 minutes)
Module assignment: Elective Module 2 of the MC4GenAI programme

Description and learning content:

In Part A of Learning Unit 2.1, you had the opportunity to experiment with AI tools for generating images. In this follow-up workshop, you will explore the phenomenon of deepfakes and engage with the following topics under the guidance of the speaker:

• what deepfakes are and the potential risks they pose
• an introduction to forensic approaches for detecting deepfakes
• AI-compressed vs. AI-generated images
• practical exercise / interactive activity: distinguishing between real, AI-compressed, and AI-generated sample images

Speaker: Sandra Bergmann

Format: On-campus workshop. The room will be announced after registration.

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “MC4GenKI)”

Prerequisite: This workshop is intended for Ohm students from all disciplines who have already gained some initial experience with ChatGPT or similar AI tools and would now like to engage more deeply in the practical development of their own solutions.

If you have had little or no experience with AI so far, we recommend first attending the foundational workshop “AI as a Learning Tool: How Lange Language Models Work, Prompting, and Critical Use in Practice” in order to achieve the best possible learning outcomes.

Date: Sat, 14 March 2026, 9:30 a.m.–5:00 p.m.
Module assignment: Elective Module 2 of the MC4GenAI programme

Description:

Which AI tools and platforms are genuinely useful for your studies? What is each tool suitable for, and what should you be aware of when using it?

In this compact Saturday workshop, you will explore a range of AI tools in short, focused practical sessions based on specific study-related scenarios: having complex content explained, researching and verifying sources, creating learning materials, preparing for exams, or organising your study routine more effectively.

Workshop structure:

• Overview and orientation
  You will receive a concise overview of the AI landscape: what categories of tools exist, what they can do, and where their limitations lie. In addition, you will be introduced to the essential fundamentals for working effectively with AI tools and for writing strong prompts.
• Hands-on testing and comparison
  In several practical sessions, you will test different tools individually or in small teams using concrete tasks drawn from everyday student life — for example, asking a tool to explain a difficult topic, checking the reliability of a research question, generating learning materials from lecture notes, or creating a study plan for the exam period. After each session, you will evaluate the results together with the other participants: what worked well, and what did not?
• Reflection and transfer
  At the end of the workshop, you will reflect on your experiences and create your personal tool compass: which tools will you continue to use for which purposes, and what do you need to keep in mind when using them? Through exchange with other participants, you will sharpen your judgement and take away further recommendations.

What will you gain?

• A practice-based overview of AI tools and platforms for your studies
• A clear sense of which tool is suitable for which purpose — and which is not
• Your personal tool compass for everyday academic life
• Greater awareness of potential pitfalls and important points to consider

Speaker: Simon Roderus

Format: On-campus workshop. The room will be announced after registration.

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → "MC4GenKI)”

Prerequisite: This workshop is open to Ohm students from all disciplines and requires no prior knowledge.

Important: This workshop is the first part of Learning Unit 2.3. If you would like to complete the full MC4GenAI programme, please also register for the second part of Learning Unit 2.3.

Date: Fri, 6 March 2026, 9:30–11:00 a.m.
Module assignment: Elective Module 2 of the MC4GenAI programme

Content: In this workshop, you will become familiar with a range of tools for AI-supported literature research, including their possibilities and limitations.

Speaker: Teaching Library of the Library

Format: On-campus workshop. The room will be announced after registration.

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “MC4GenAI”

Prerequisite: This workshop is intended for students from all disciplines who are seeking guidance on the use of AI and who wish to shape their role as authors in the digital age in a conscious and reflective way. Participation in the complementary workshops on literature research (Part A) and academic writing (Part B, including the use of tools such as Copilot) is strongly recommended.

Date: Fri, 6 March 2026, 11:15 a.m.–1:00 p.m.
Module assignment: Elective Module 2 of the MC4GenAI programme

Important: This workshop is the third part of Learning Unit 2.3. If you would like to complete the full MC4GenKI programme, please also register for Parts A and B of Learning Unit 2.3.

Content:

AI tools can support literature research, structuring, and text production. At the same time, they raise important questions:

• Should I use AI?
• How can I use it meaningfully?
• What are the opportunities and limitations of AI in academic work?
• What still counts as independent work when I use AI?

This workshop offers an introduction to academic writing with AI support. Its central aim is to help participants develop their own reflective and well-founded approach. We will examine key stages on the path towards a term paper — from finding a topic and developing a structure to formulating text — and will explore the use of AI tools through selected practical exercises.

From the perspective of teaching staff, the workshop will also address the role that AI-related competencies may play in the assessment of academic work, as well as expectations regarding transparency and reflection.

You are welcome to bring current term papers and/or paper topics in PDF or Word format.

Learning outcomes

The workshop will enable you to:

• classify the basic functions and possible uses of AI in the academic writing process
• evaluate the opportunities, limitations, and quality criteria of AI use in individual phases of writing a term paper
• apply basic strategies, such as prompt design and the critical evaluation of AI-generated outputs, in exemplary ways
• reflect on your own use of AI in your studies and position yourself consciously and responsibly

Speaker: Prof. Dr Carolin Freier, Faculty of Social Sciences

Format: On-campus workshop. The room will be announced after registration.

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “MC4GenKI”

Prerequisite: This workshop is open to Ohm students from all disciplines and requires no prior knowledge.

Important: This workshop is the second part of Learning Unit 2.3. If you wish to complete the full MC4GenAI programme, please also register for the other parts of Learning Unit 2.3.

Date: Thu, 19 March 2026, 2:00–5:00 p.m.
Module assignment: Elective Module 2 of the MC4GenAI programme

Description:

On the one hand, the workshop addresses how the AI tool Copilot can support different phases of the writing process, such as analysing literature, drafting initial text, and revising written work (How can this tool be used effectively?).

On the other hand, Copilot itself will be examined as a subject of learning, focusing on questions such as:

• How should I deal with the results generated by Copilot? What can I learn from them?
• How can Copilot serve as a meaningful companion in the writing process?
• How can the outputs generated by Copilot be critically evaluated?
• What legal issues (e.g. data protection, copyright, and study/examination regulations) arise from using such tools?
• What responsibilities do users assume when working with AI tools such as Copilot?

During the workshop, participants will practise working with AI tools through selected examples. Outputs generated by other AI tools (e.g. ChatGPT, Gemini, etc.) will also be critically reviewed and evaluated.

Speaker: Schreibzentrum

Format: Online workshop. The link will be provided after registration.

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “Key Competencies: Writing”

Prerequisite: This workshop is open to Ohm students from all disciplines, including those with no prior knowledge.

Date: Tue, 10 March 2026, 9:00 a.m.–5:00 p.m.
Module assignment: Elective Module 2 of the MC4GenAI programme

Description:

You do not need to be able to “program perfectly” in order to get started: in vibe coding, you use AI as a co-developer. Together, we will turn ideas into real web applications, including both frontend and backend components. Afterwards, you will work on your own project, describe it in natural language, and use free tools to get your code up and running quickly.

Content:

• Live demonstration: from idea to web application (frontend and backend)
• Independent creative work by participants: ideas are outlined and formulated in natural language, from which functional code is generated directly
• Development and testing are carried out using free web services

Speaker: Yilmaz Duman

Format: On-campus workshop. The room will be announced after registration.

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “Generative AI (MC4GenAI)”

Prerequisite: This workshop is open to Ohm students from all disciplines.

Date: Fri, 13 March 2026, 9:00 a.m.–max. 5:00 p.m.
Module assignment: Elective Module 2 of the MC4GenAI programme

Description:

Following the success of DeepSeek, so-called reasoning language models have come into focus. Unlike classical large language models (LLMs), these models do not only provide answers but also make their intermediate reasoning steps transparent. This workshop explains how such models work and how they differ from conventional LLMs.

Content:

• Fundamentals of language models
• Encoder and decoder models
• Generative language models for text continuation
• Chat templates for answering questions
• Reasoning models and their key differences
• Prompting reasoning models
• Controlling the level of detail in reasoning processes
• Advantages and limitations of reasoning models

Speaker: Prof. Dr Christian Winkler

Format: On-campus workshop. The room will be announced after registration.

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “Generative AI (MC4GenAI)”

AI-Supported Applications: Concepts, Architecture, and Typical Patterns (RAG, Tool Calling, etc.)
With a practical component: From LLMs to AI functionalities using tools and context

Prerequisite: This workshop is open to Ohm students from all disciplines. A basic understanding of programming is advantageous, as the workshop takes a more technical approach and addresses both architectural and implementation-related aspects.

Date: Thu, 12 March 2026, 9:00 a.m.–max. 5:00 p.m.
Module assignment: Elective Module 2 of the MC4GenAI programme

Content:

This workshop provides a well-founded introduction to AI-supported applications. We will examine what large language models (LLMs) do well, where their limitations lie, and why AI systems in practice only become truly capable of acting through architectural components such as tool calling (function calling), retrieval-augmented generation (RAG), and orchestration. In this context, we will explore typical patterns that enable AI to retrieve information reliably, use external services, and deliver structured results.

In the practical part of the workshop, participants will apply what they have learned directly by adapting and extending an existing application in a targeted way. This includes integrating tool calls, improving contextual grounding (e.g. through documents or data sources), and refining system behaviour through suitable guardrails for safety and robustness, such as protection against prompt injection, data leakage, and system misbehaviour. The aim is for you to understand the key building blocks and approaches required to integrate AI functionality into applications in a meaningful and effective way.

A basic understanding of programming is beneficial, as the workshop is technically oriented and addresses both architectural and implementation-related aspects. The workshop will work with TypeScript.

If you would like to participate actively in the hands-on part and run the workshop project locally, you should bring a laptop on which Node.js can be executed.

Speakers: Thomas Flander and Martin Geissler, ISO Public Services GmbH

Format: On-campus workshop. The room will be announced after registration.

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “Generative AI (MC4GenAI)”

Prerequisite: This self-study unit is intended for participants in MC4GenAI who plan to complete the full MC4GenAI programme.

Date: Self-paced; timing is determined by the learners themselves
Format: Self-study unit via Moodle. The link to the Moodle course will be sent to participants on 20 March 2026.
Module assignment: Module 3 of the MC4GenAI programme

Description:

Module 3 constitutes the guided reflection phase within the MC4GenAI learning pathway. Building on the experiences gained in Modules 1 and 2, students develop an individual learning journey in the field of generative AI. In doing so, the module particularly strengthens self-directed learning skills, reflective capacity, and lifelong learning in the age of AI.

Learning outcomes:

After completing the course, students will be able to:

• analyse and identify gaps in their knowledge as well as areas of interest within the field of generative AI in relation to their studies and intended professional field
• distinguish between different types of online educational offerings on generative AI (including OER and MOOCs, e.g. KI-Campus) and assess their potential for their own further development
• research, select, and evaluate suitable OER and MOOC offerings in a goal-oriented way, particularly with regard to relevance, quality, currency, and personal learning objectives
• develop an individual learning plan (learning journey) for the further development of their own AI competencies
• explain the importance of lifelong learning, including informal learning, for the continuous development of AI competencies and make productive use of it for their own competence development

Learning content:

• Identifying personal learning needs in the field of generative AI
• Exploring the range of online educational offerings on generative AI (OER and MOOCs, e.g. KI-Campus)
• Researching, selecting, and evaluating suitable online learning opportunities
• Reflecting on and refining an individual learning plan for independent further study

Speaker: Thu Van Le Thi

Registration via VirtuOhm → “Course Registration” → Category “Teaching and Competence Development” → “Generative AI (MC4GenAI)”

Prerequisite: Participation in the final workshop requires successful completion of Modules 1 to 3.

Registration: via email to thuvan.lethi@th-nuernberg.de

Date: The final workshop and the awarding of micro-credentials will take place in July/August 2026 (after the examination period). The exact date will be arranged in consultation with the participants.

Format: Workshop (online or on campus)

It is possible to complete the MC4GenKI programme within one semester. Participants may also spread the programme over two to three semesters. The learning units are scheduled in compact programme periods, enabling participants to complete them within a relatively short timeframe.

Participants may choose and attend individual topics or workshops according to their needs and interests. To do so, they should register for the relevant workshops individually via VirtuOhm. If they wish to obtain the programme qualification, they are required to complete the full programme.

In Module 2, participants are required to choose and complete at least three learning units, depending on their interests. If desired, they may also select and attend additional learning units. Please note that early registration for the learning units in Module 2 is strongly recommended.