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Target audience
Digital skills for allDigital technology / specialisation
Web Development SoftwareDigital skill level
Basic Intermediate AdvancedGeographic Scope - Country
MaltaIndustry - Field of Education and Training
Generic programmes and qualifications not further defined Basic programmes and qualificationsTarget language
EnglishType of initiative
Local initiative
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Persons in tertiary education (EQF 6)Typology of training opportunities
Course
Learning activity
lab / simulation / practice coursework
Assessment type
OnlineTraining duration
Up to 1 week
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DiHubMTIs this course free
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No
Type of training record
Single offer
Training Start date
2026
Effort
Part time light
Credential offered
Learning activity
Self-paced course
No
URL
https://dihubmt.eu/training-courses/llm-lecture-series-how-large-language-models-work-round-3/
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LLM Lecture Series: How Large Language Models Work Round 3
- October 23, 2026
- Andrew
Duration
7 Sessions (2 hours each)
Focus
| Understanding the architecture, training, and computational mechanics of large language models and Transformers. |
Target
ICT professionals, engineers, developers, and technically curious professionals and graduates.
Module Overview
Module 1 – Introduction to LLMs (2 lectures/4 hours)
- AI and ML foundations, language models, the rise of Transformers, emergent properties, and the AGI debate.
Module 2 – Preliminary Concepts (1 lecture/2 hours)
- Neural networks, the error back propagation algorithm, sequence modelling, loss functions, softmax, NER, and key NLP tasks.
Module 3 – Work Embeddings (1 lecture/2 hours)
- Word2Vec, GloVe, FastText, contextual embeddings, and practical embedding workflows.
Module 4 – How ChatGPT Works and is Trained (2 lectures/4 hours)
- GPT-style Transformers in detail: positional encodings, Q-K-V attention, residuals, normalisation, projection layers, model training, fine-tuning, hallucination, and the way forward.
Materials provided
- Full slide deck for all lectures (made available to registered attendees)
- Slides include worked diagrams and step-by-step breakdowns of the Transformer and Q-K-V computations
- Curated references for further study
Dates
- Tuesday, 1st September 2026
- Thursday, 3rd September 2026
- Thursday, 10th September 2026
- Tuesday, 15th September 2026
- Thursday, 17th September 2026
- Tuesday, 22nd September 2026




