Location: Online
Teaching Language: Turkish (with English subtitles)
Organizing Institution: TÜBİTAK
Level: Intermediate
Format: Asynchronous
Industrial domains: Cross-sectoral: public sector, finance, manufacturing and industry, retail and e-commerce, energy, health, communications and media, other sectors
Course description:
A hands-on, non-technical course on getting consistently better results from generative AI tools at work. Participants learn a reusable six-building-block prompt template, how to diagnose and fix the four most common prompt failures, techniques that raise output quality, the red lines of data safety, and how to turn good prompts into repeatable team workflows with human review gates.
Prerequisites:
Basic AI literacy: familiarity with concepts such as large language models, hallucination and bias, for example through the introductory course of this training series or equivalent. No coding or technical background is required.
Learning Outcomes:
After completing the course, participants can:
- write structured, reusable prompts for their own business tasks using the six-block template
- diagnose weak AI outputs, identify the missing building block and correct it through a fast iteration loop
- apply data-safety rules in daily use, keeping personal data, trade secrets and credentials out of unapproved tools
- select automation candidates with the frequency-structure matrix, set up a team prompt library, and run three workflow patterns (meeting minutes, inbox and document triage, periodic reporting) with human oversight, measuring the time and quality gains
Agenda:
Module 1: Strategic prompt architecture (the brilliant-intern model, how LLMs read your words, the six building blocks: role, context, task, format, constraints, examples; a reusable template)
Module 2: Diagnosing bad outputs (four common failures and their fixes, the iteration loop, quality boosters, data-safety red lines)
Module 3: From one good prompt to a working system (what to automate, the team prompt library, three ready workflow patterns, human review gates, measuring the gain)
Instructor Name: Dr. Doğu SIRT
Dr. Doğu Sırt has been a lecturer at the Faculty of Computer and Informatics at Istanbul Technical University since 2015. He holds degrees in computer engineering and business administration, a master's degree from Gebze Technical University, and a PhD in computer engineering from the National Defence University (2023). Alongside his academic work, he is a corporate trainer, delivering courses on Python programming, artificial intelligence, data science, and data engineering for universities, public institutions, and the private sector. He also serves as a project referee and consultant for KOSGEB, ITU ARI Teknokent, and 1773 Teknokent, supporting the entrepreneurship ecosystem. His work focuses on integrating AI into business processes and turning AI into a strategic element that creates sustainable business value.
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Disclaimer
Only participants who live and/or work in EuroHPC JU participating countries can take part in the event (https://eurohpc-ju.europa.eu/about/discover-eurohpc-ju_en).
For registration purposes, only official email addresses will be accepted. Personal or generic email addresses (e.g., Gmail, Hotmail, Yahoo) are strictly not permitted.
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Acknowledgements
This event was supported by the BSC AI Factory project, which received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101234399 and Spain, Portugal, Romania and Türkiye. The JU receives support from the European Union’s Horizon Europe Programme.
