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Databricks: Large Language Models: Foundation Models from the Ground Up

This course dives into the details of foundation models in large language models (LLMs). You will learn the innovations that led to the proliferation of transformer-based models, including BERT, GPT, and T5, and the key breakthroughs that led to applications such as ChatGPT. Additionally, you will gain understanding about the latest advances that continue to improve LLM functionality including Flash Attention, LoRa, AliBi, and PEFT methods.

Large Language Models: Foundation Models from the Ground Up
4 weeks
4–8 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

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Starts Apr 26
Ends Jun 1

About this course

Skip About this course

This course dives into the details of LLM foundation models. You will learn the innovations that led to the proliferation of transformer-based architectures, from encoder models (BERT), to decoder models (GPT), to encoder-decoder models (T5). You will also learn about the recent breakthroughs that led to applications like ChatGPT. You will gain understanding about the latest advances that continue to improve LLM functionality including Flash Attention, LoRa, AliBi, and PEFT methods. The course concludes with an overview of multi-modal LLM developments to address NLP problems involving a combination of text, audio, and visual components.

At a glance

  • Institution: Databricks
  • Subject: Computer Science
  • Level: Advanced
  • Prerequisites:
    • Intermediate-level experience with Python

    • Understanding of deep learning concepts and hands-on experience with PyTorch

    Completing the LLM: Application through Production course is highly recommended, but not strictly required prior to taking this course.

  • Language: English
  • Video Transcript: English
  • Associated programs:
  • Associated skills:Natural Language Processing, Transfer Learning, Decision Making

What you'll learn

Skip What you'll learn
  • Describe the components and theory behind foundation models, including the attention mechanism, encoder and decoder architectures.
  • Articulate the developments in the evolution of GPT models that were critical in the creation of popular LLMs like ChatGPT.
  • Explain and implement the latest advances that improve LLM functionality, including Fast Attention, AliBi, and PEFT methods.
  • Gain insights into multi-modal applications of Generative AI (GenAI) / LLMs involving a combination of text, audio, and visual elements.
  • Module 1 - Transformer Architecture: Attention & Transformer Fundamentals

  • Module 2 - Efficient Fine Tuning

  • Module 3 - Deployment and Hardware Considerations

  • Module 4 - Beyond Text-Based LLMs: Multi-Modality

Who can take this course?

Unfortunately, learners residing in one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. edX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.

This course is part of Large Language Models Professional Certificate Program

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Expert instruction
2 skill-building courses
Self-paced
Progress at your own speed
3 months
4 - 9 hours per week

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