Training Information

• Duration: 2 Days (Day 1 Theory, Day 2 Practice)
• Level: Beginner / Advanced
• Participant Profile: Corporate Employees, University Students, Individual Participants

Purpose of the Training

Artificial intelligence today has become not only a technology but also a kind of "professional/personal assistant" that simulates our cognitive capabilities and in some cases, even surpasses them. This training aims to help institutional employees view this change not as a threat, but as an opportunity to enhance their careers. Participants will understand the logic behind AI and learn how to integrate the technology into their business processes, becoming conscious and willing stakeholders in the institution's digital transformation journey. Our goal is to overcome fear with knowledge and to train visionary professionals who combine human intelligence with machine power.

• Day 1: Theoretical Framework, Concepts, History, and Ethics/Responsible Management (Mindset Transformation)
• Basics and the Big Picture
• Data and Human Relations (Cooperation, not Competition): The role of data in the digital world, human factor, and data literacy. Synthesis of human creativity with machine processing power.
• Basics of Artificial Intelligence: Data, Hardware, Software
• The "Short History" of AI and Why Now?: The development process from the past to the present, the transition from AI winter to spring. Technological breakthrough points and why "today" is the best time to catch this wave.
• Conceptual Depth and Responsibility
• Introduction to Prompting: How do Large Language Models (LLM) think? The communication language with machines, context creation, and the theoretical infrastructure of prompt logic.
• AI and Ethics (Power and Responsibility): Copyrights, the risks of "hallucination" (delusion), data privacy (Personal Data Protection Law/GDPR compliance), and critical ethical frameworks for bias-free usage.
• Day 2: Practical Workshop and Tool Usage (Practical Transformation)
• Content Management with Generative AI
• Prompt Engineering Applications: Transition from theory to practice. Techniques for effective prompt writing (Zero-shot, Few-shot). JSON prompt usage examples and benefits.
• Text Generation with Generative Language Models: Real-time scenarios on LLMs. Creating email, report, summaries, and crisis communication texts.
• Personalizing Language Models: Adjusting and optimizing standard models to fit the organizational culture or project needs (Custom Instructions).
• Visualization and Specialized Solutions
• Creating Visuals with Generative AI: Text-to-Image conversion technologies. Practicing creating presentation materials and project visuals with current AI tools.
• Specialized Language Models: Examining models specialized for sectors such as real industries, supply chains, and finance.
• Closing Session: Participants will prepare a mini "Transformation Plan" for their own business processes using the tools they have learned.

Training Outcomes

• Strategic Vision: Participants will gain an understanding of the historical development of AI technologies and the underlying concepts, enabling them to see the big picture.
• Application Competence: By applying current "Prompt Engineering" techniques, participants will gain the ability to obtain high-quality, purpose-oriented outputs from AI.
• Increased Efficiency: Participants will save time by integrating text and visual production tools into their workflows.
• Conscious Usage: Participants will develop a habit of safe AI usage, being aware of ethical risks, legal boundaries, and data privacy.
• Data Awareness: Participants will gain awareness of the importance of data privacy, the significance of personal and corporate data, and the key considerations in interacting with AI software.
• This training will provide both theoretical knowledge and practical skills that can be used the "next day" in personal life or at the office.

Training Notes

• The trainer will adapt the content according to the dynamics of the participant group (sector-specific corporate or academic).
• The training is designed with a format where the first day solidifies conceptual foundations and the second day is interactive with participants actively creating on their computers.
• The program is based on general generative AI principles, without being tied to any specific tool.
• Upon request, a 2-hour online "Training Efficiency Follow-Up Session" can be held with participants within 1 month after the training.
• At the end of the training, participants will receive a university-certified certificate.