Introduction to Large Language Models
1h 17mIntermediate2025-03-13
Authors

Jonathan Fernandes
Consultant focusing on data science, AI, and big data
Course details
Large language models (LLMs) have taken the AI world by storm. LLMs are behind some of the biggest AI technologies over the last few years, like ChatGPT and GPT-4. In this course, Jonathan Fernandes provides an overview of LLMs suitable for technical learners and non-technical learners alike. Jonathan shows you what LLMs are and what you can do with them, and takes a look under the hood so you can understand why they work the way they do and how they can affect your work. He explains how LLMs are trained and details the components of LLMs, and then takes a look at several different applications of LLMs—including Google’s BERT, GPT-3, PaLM and PaLM 2, ChatGPT and GPT-4, and Llama—and shows you how to compare LLMs using benchmarks.
Skills covered
GPTChatGPTNatural Language Processing (NLP)OpenAIIntroduction toArtificial Intelligence (AI)
Concepts
0. Introduction
- 01 - The impact and functionality of large language models
1. Transformers in NLP
- 02 - What are large language models
- 03 - How are large language models trained Pre-training
- 04 - Making large language models follow instructions
2. Large Language Model Components
- 05 - Transformer architecture
- 06 - What are parameters
- 07 - What are tokens
- 08 - What are context lengths
3. Large Language Models
- 09 - BERT
- 10 - Scaling laws
- 11 - GPT-3
- 12 - Chinchilla
- 13 - PaLM and PaLM 2
- 14 - ChatGPT and GPT-4
- 15 - Open LLMs
- 16 - Comparing LLMs
- 17 - GitHub Models - Comparing LLMs
- 18 - Accessing large language models using an API
- 19 - LLM trends
Conclusion
- 20 - Going further with large language models
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