Introduction to Large Language Models (Pilot)

Type of course:

Digital learning, Lesson

Language:

Duration:

15 minutes

Workload:

Array hour

Proficiency:

Intermediate

Target:

Professionals, Manager, Students

SUMMARY

In this lesson, we will explain in detail how Large Language Models (LLMs) operate and their role in Digital Twin technology. This introduction to LLMs will demonstrate how these AI models enhance communication with digital systems, enabling natural language tasks like summarization, text generation, and decision-making. Three types of LLMs approaches or algorithms will be explained in detail to state the differences between encoder-only, decoder-only, and encoder-decoder LLMs. Following this, we will discuss the topic and use of fine-tuning LLMs and how this can be done in Python. With this foundation, learners will be able to decide which type of LLM is suitable for different kinds of applications where human-machine communication is necessary in digital systems.

About The Author

Software Competence Center Hagenberg (SCCH), is a research organization committed to building the bridge between fundamental research and industry. With more than 20 years of experience, SCCH has been bringing the highest value to academic research by implementing feasible solutions to companies around Europe in light of Industry 5.0 and the rise of artificial intelligence. We are composed of a great team of data and software scientists from Austria and many other nationalities, with great experience not only in technical development and implementation but also highly motivated to train our customers to use our solutions.

Learning outcomes

By the end of this lesson, students will be able to explain how Large Language Models are used for the purpose of human-machine interaction in the era of Digital Twins.
By the end of this lesson, the learner will ble able to distinguish between encoder-only, decoder-only, and encoder-decoder Large Language Model architectures and decide which architecture is suitable for which type of digital system for communication.
By the end of this lesson, students will be able to explain the concept of fine-tuning a Large Language Model (LLM) and access a Python library suitable for this purpose.