Large Language Models Essentials

Course The course is aimed at decision-makers and interested parties who want to gain a basic understanding of Large-Language Models (LLM) and their applications. The course is deliberately designed to be efficient and short to allow busy people to learn the most important things about these new tools in just four hours. The primary course content is theory on the function, strengths and weaknesses of LLM, supplemented by practical exercises with OpenAI’s GPT models.

Upcoming Course Dates
  • 25.11.2024, 13:00 - 17:00, Online (Virtually) Language: German. Costs: CHF 500 (ca. 510 Euro)

Early-Bird discount: Up to 1 month before the course starts 10%. Up to 25% discount for group bookings. No VAT will be charged. → To registration

Further dates will be set according to demand. If you are interested, please get in touch (→ Contact) without obligation, so that I can inform you and to simplify the course planning (place and time).

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Prerequisites No prior knowledge is required. Initial experience in using an LLM (e.g. ChatGPT) is an advantage, but not essential.

Organizational Half-day course with a maximum of 10 participants (except for online courses). Participants receive a certificate of attendance and all course materials (slides) in digital form.

Detailed course description The main objectives of the course are to learn basic vocabulary and use cases of large language models. Furthermore, the discussion of (unfortunately often neglected) risks and weaknesses is of central importance.

Examples of concepts covered include:

  • How does an LLM basically work?
  • The problem of missing current and private data during training. Retreiver augmented generation (RAG) as a possible solution.
  • LLM fine-tuning: explanation, advantages and disadvantages.
  • Costs in LLM: Why are they so expensive and how can savings be made?
  • Brief introduction to data privacy with LLMs
  • Advantages and disadvantages of open source models
  • Document search with LLMs: Embeddings/vector search
Conditions For course content, booking and cancellation conditions and more, see Legal.