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Generative AI: Introduction to Large Language Models

Generative AI: Introduction to Large Language Models

1h 36mIntermediate2023-11-13

Authors

Frederick Nwanganga

Frederick Nwanganga

Information Technology Professional and Teacher

Course details

Generative AI tools such as ChatGPT, DALL-E, Bard, and Stable Diffusion have received a lot of press, as of late. In this course, information technology professional and teacher Fred Nwanganga provides learners with a gentle introduction to what these tools are, how they work, and how they fit into the larger AI ecosystem. Explore generative AI with large language models (LLMs). Learn what generative AI and LLMs are, what types of LLMs exist, and how they have evolved. Dive into neural networks, including how they learn and an overview of deep learning and its transformative impact. Discover the building blocks of LLMs, such as the transformer architecture, encoders and decoders, the attention mechanism, and self–attention. Plus, go over the societal implications of LLMs.

Skills covered

Natural Language Processing (NLP)Generative AIArtificial Intelligence (AI)One-Off

Concepts

0. Introduction

  • 01 - Generative AI with large language models

1. Large Language Models

  • 02 - What is generative AI
  • 03 - What is a large language model
  • 04 - Types of large language models
  • 05 - The evolution of large language models

2. Neural Networks and Language Models

  • 06 - What is a neural network
  • 07 - How do neural networks learn
  • 08 - Deep learning and its significance

3. Building Blocks of Large Language Models

  • 09 - The Transformer architecture
  • 10 - What is an encoder-decoder
  • 11 - The attention mechanism
  • 12 - How does self-attention work

4. Societal Implications of Large Language Models

  • 13 - Common applications of large language models
  • 14 - Challenges with large language models
  • 15 - The future of large language models

Conclusion

  • 16 - Next steps

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