Introduction & Principles of Generative AI for the Workplace
Optimize Your Workflows: Master Generative AI for Professional Management.
In today’s organizational landscape, managing vast amounts of documentation and complex internal processes is a constant challenge. This two-day intensive course at the TU Berlin Academy bridges the gap between cutting-edge technology and excellent administrative work. Designed specifically for professionals without a background in computer science, this course will give you a clear, practical understanding of how Large Language Models (LLMs) can transform your daily work. From automating report summaries to optimizing internal communication and designing smart workflow tools, you’ll learn how to use generative AI responsibly and effectively. Take the leap into the future of administration and make AI your most reliable co-pilot.
Course Content
- What is AI?
- What is generative AI?
- Overview of current AI technologies
- Large Language Models (LLMs) and their capabilities
- Opportunities and limitations of AI systems
- AI in organizational settings
Learning Goals
- Understand the basic concepts of artificial intelligence and generative AI.
- Grasp the principles behind large language models (LLMs).
- Interact effectively with AI systems using structured prompting techniques.
- Understand the basic principles of Python programming in the context of AI-powered tools.
- Explore how AI can support administrative and organizational tasks.
Participation & Requirements
- Target Group
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This course is intended for project managers, policy analysts, executives, and team leaders, as well as public sector employees and administrative staff.
- Prior Knowledge
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No prior knowledge of programming, computer science, or AI is required.
- Technical requirements
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For the hands-on exercises, you must have your own laptop with administrator privileges (to install specific programs).
- Certificate Details
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Upon successful completion, you will receive a certificate of completion from TU Berlin.
This course is recognized in accordance with Section 10(5) of the Berlin Educational Leave Act (BiZeitG).
Instructors
Prof. Dr. Hamid Mostofi is a professor of data science and artificial intelligence at SRH Berlin University of Applied Sciences and a senior researcher and project manager at TU Berlin, focusing on the application of AI in business and socioeconomic contexts.
His research interest lies in the application of data science techniques and artificial intelligence to sustainability concepts, taking into account social acceptance, perception, and attitude, as well as socio-economic factors.
He completed his PhD at TU Berlin with the grade "Summa cum laude." During his PhD, he worked as a research assistant at TU Berlin and was involved in the projects by the Federal Ministry for the Environment (BMU) and Federal Ministry for Economic Affairs and Climate Action (BMWK).
Currently he is the work package leader of MDZT (Mittelstand-Digital Zentrum Tourismus) funded by Federal Ministry of Economic Affairs and Energy BMWE since 2024 which is working on empowering SMEs by application of AI and digitalisation in Germany. Also. he wasthe visiting researcher by the University of California, Berkeley (UC Berkeley).
University-based continuing education, designed for real-world application
Our courses are developed within the academic departments of TU Berlin and are taught by people who conduct research and work in their respective fields.
The content is drawn from research topics at TU Berlin and beyond and is presented in high-quality course formats.
Apply your knowledge directly in the course and explore your professional challenges and questions.
A certificate of participation from the Technical University of Berlin, a University of Excellence within the Berlin University Alliance.
Recognized as educational leave in Berlin. Employees are granted up to 5 days off from work for continuing education.
„The thorough theoretical instruction gives me the confidence I need to strategically assess AI technologies and apply them efficiently and responsibly in my day-to-day work.“