Getting Started with Large Language Models (LLMs)

Generative AI    |    Intermediate
  • 13 videos | 1h 36m 20s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Dive deep into the expansive realm of large language models (LLMs), a pivotal cornerstone in today's artificial intelligence (AI)-driven landscape. This course unravels the intricacies of these models, from their architecture and training methods to their profound implications in real-world scenarios. Begin by exploring the significance of LLMs in the world of AI. Then you will examine the architecture of LLMs, evaluate the impact of data on the effectiveness of LLMs, and fine-tune your LLM for a specific task. Next, you will investigate the ethical implications of using LLMs, including potential biases and privacy issues. Finally, you will discover the potential and limitations of LLMs and learn how to stay updated with the latest advancements in this dynamic field.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Define large language models and outline their significance in the world of artificial intelligence (ai)
    Outline the key components and general architecture that make up typical llms
    Contrast the pre-training methods used in training llms
    Evaluate how data size and quality can significantly impact the effectiveness of llms
    Provide an overview of the techniques used to adapt a generic pre-trained model for a specific task or application
    Outline the ethical challenges surrounding large language models, including potential biases and privacy issues
  • Use a pre-trained language model for text generation and recognize its constraints
    Assess the primary limitations and challenges, like computational requirements, that come with training llms
    Provide an overview of how llms are transforming various sectors, including natural language processing, chatbots, and translation
    Describe the current techniques employed to reduce biases in llms and to ensure fair language generation
    Describe the latest research and advancements, like model compression, in the domain of llms
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 33s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 10m 3s
    After completing this video, you will be able to define large language models and outline their significance in the world of artificial intelligence (AI). FREE ACCESS
  • Locked
    3.  Architecture of LLMs
    5m 54s
    Upon completion of this video, you will be able to outline the key components and general architecture that make up typical LLMs. FREE ACCESS
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    4.  Pre-training Approaches
    9m 13s
    In this video, we will contrast the pre-training methods used in training LLMs. FREE ACCESS
  • Locked
    5.  Impact of Data on Performance
    6m 26s
    After completing this video, you will be able to evaluate how data size and quality can significantly impact the effectiveness of LLMs. FREE ACCESS
  • Locked
    6.  Fine-tuning LLMs
    11m 12s
    Upon completion of this video, you will be able to provide an overview of the techniques used to adapt a generic pre-trained model for a specific task or application. FREE ACCESS
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    7.  Ethical Implications of LLMs
    9m
    After completing this video, you will be able to outline the ethical challenges surrounding large language models, including potential biases and privacy issues. FREE ACCESS
  • Locked
    8.  LLMs and Text Generation
    8m 59s
    In this video, learn how to use a pre-trained language model for text generation and recognize its constraints. FREE ACCESS
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    9.  Challenges in Large Model Training
    7m 50s
    In this video, we will assess the primary limitations and challenges, like computational requirements, that come with training LLMs. FREE ACCESS
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    10.  Applications of LLMs
    8m 45s
    Upon completion of this video, you will be able to provide an overview of how LLMs are transforming various sectors, including natural language processing, chatbots, and translation. FREE ACCESS
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    11.  Bias Mitigation in LLMs
    10m 39s
    After completing this video, you will be able to describe the current techniques employed to reduce biases in LLMs and to ensure fair language generation. FREE ACCESS
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    12.  Research and Advancements in LLMs
    7m 2s
    Upon completion of this video, you will be able to describe the latest research and advancements, like model compression, in the domain of LLMs. FREE ACCESS
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    13.  Course Summary
    45s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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