Gen AI in practice: How to grasp artificial intelligence in a clear, practical and value-added wayIn a world where artificial intelligence is talked about every day, the question remains open for many companies: how to use it realistically and effectively in practice? With two professionals who are dedicated to AI, we have created a practically focused course ‘Gen AI in practice’.
Synergy of two perspectives
The course with workshop is led by Ján Grexa (FBE) and Daniel Skala (Cisco, NL):
Ján helps people from both manufacturing and service companies to identify specific areas where AI will make their daily work more efficient.
As an AI engineer, Daniel has been involved in developing features that are now used by thousands of Cisco users around the world.
Their collaboration brings a unique synergy to the course – a combination of understanding our business environment while having access to the latest technologies. The result is actionable inspiration that companies can immediately apply in their own environments.
The course is designed for anyone who wants to understand, test and implement artificial intelligence in a corporate environment – with an emphasis on practical applicability.
What will participants gain?
In the introduction, they will learn about the differences between different AI models – how large language models work and how closed solutions like GPT-4, Gemini or Claude differ from open-source alternatives like LLaMA or Phi. We’ll also look at so-called reasoning models and how their reasoning capabilities differ. An important part of this will be multimodal models that work with image, sound or other inputs in addition to text.
The second part of the course focuses on navigating the current ecosystem of AI tools. Participants will be introduced to practical solutions such as ChatGPT, GitHub Copilot, DeepL, Midjourney, DALL-E or Apple Intelligence. We will demonstrate how to use these tools to work with different types of data – from text documents to databases to visual and audio content. We’ll also discuss concepts like GPTs, DeepResearch, Agents or Canvases – tools and features that allow AI to be tailored to specific work needs.
One of the key themes of the course is prompt engineering – that is, the art of correctly specifying questions and commands to AI models. We will introduce specific techniques that lead to more accurate and practical outputs. Participants will learn, for example, Chain of Thought, ReAct prompting, few-shot approaches or role prompting, and we will also show methods for the model to self-correct its outputs using self-criticism.
Workshop and case studies
Finally, there is a hands-on workshop and real case studies. Participants will go through their own situations, design their own use of AI in their work and get feedback. There is also inspiration from different companies – from manufacturing companies to financial services. The basic principle remains the same: AI should adapt to the company, not the other way around.In the hands-on workshop, participants will try working with AI tools first-hand – from generating content, to creating assistants, to using ChatGPT as a search engine, consultant or personal tutor. We’ll look at how to integrate AI into everyday processes and where it makes the most sense to start – whether in administration, analysis, communication or planning.
Who is the course for?
The course is ideal for managers, analysts, engineers, specialists and team leaders who want to:
- get an overview of AI technologies without the need for programming,
- understand where AI has real benefit in the business,
- start testing and implementing specific tools in their work.
Previous FBE events in this area have been attended by experts from manufacturing companies such as Volkswagen Slovakia, IAC Group, Slovnaft, Porsche Werkzeugbau, ArcelorMittal Gonvarri SSC Slovakia, Panasonic, Inter IKEA Group, Foxconn, as well as services from UNIQA Insurance Group, ČSOB Financial Group and others.
Workshop and case studies
The final part is a practical workshop and real case studies. Participants will go through their own situations, design the use of AI in their work and get feedback
