Course Objective This course is designed for professionals, decision-makers, and interested individuals who want to stay up-to-date with the latest AI developments. It provides a structured overview of recent advances and trends in Artificial Intelligence. After completing the course, participants will:

• understand the latest developments in Large Language Models (LLMs) and their applications.
• have a fundamental understanding of AI Agents and their potential for automation processes.
• comprehend the benefits of multimodal capabilities in modern AI systems.
• learn about the advantages and applications of Small Language Models (SLMs).

• No course currently scheduled. Please contact me if you are interested so I can notify you when new course dates are published.

Early-bird discount: 20% up to 2 months before course start, 10% up to 1 month before course start. No VAT charged. → Register now

The next dates will be determined based on demand. If you are interested, please contact me (→ Contact) so I can inform you and to facilitate course planning (location).

Prerequisites Basic knowledge in the field of Large Language Models is required, such as that provided in the courses Quickstart: Artificial Intelligence, Understanding Artificial Intelligence, or Large Language Models Essentials. This prior knowledge will enable better understanding and contextualization of advanced concepts and current developments.

Organization Half-day intensive course (4 hours) with a maximum of 15 participants. Participants receive a certificate of attendance and all course materials (slides) in digital format. The course is regularly updated to cover the latest developments in AI.

Detailed Course Description The half-day course “Trends in AI” offers a compact yet in-depth look at the latest developments in Artificial Intelligence. The content is continuously updated to reflect the most recent trends.

Current Focus Areas:

1. Advances in Large Language Models (LLMs)

   • The newest generation of LLMs (GPT-4o, Claude 3, Gemini, Llama 3)
   • Multimodal capabilities: text, image, audio, and video
   • Improvements in reasoning, consistency, and knowledge accuracy
   • Practical applications and their economic viability

2. AI Agents - The Next Evolution

   • From passive assistants to proactive agents
   • Autonomous actions and decision-making
   • Agency systems and collaborative AI
   • Application examples: research assistants, coding agents, autonomous business processes

3. Small Language Models (SLMs) - The Efficient Alternative

   • Benefits of local execution and data privacy
   • Performance capabilities and limitations compared to LLMs
   • Application areas for resource-constrained environments
   • Brief practical insight into Ollama software

The course combines theoretical content with practical demonstrations and discussions. Participants have the opportunity to bring in their own questions and use cases.