What you should know

Contents

• Introduction Introduction

  • Principles and practical applications of NLP and LLMs

    46s
  • What you should know

    37s
• 1. Introduction to NLP and LLMs 1. Introduction to NLP and LLMs

  • What is natural language processing (NLP)?

    1m 3s
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    Why process text data?

    4m 42s
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    Understanding large language models (LLMs)

    2m 2s
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    Key elements of LLMs

    5m 42s
• 2. NLP and LLMs Use Cases 2. NLP and LLMs Use Cases

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    Identifying opportunities for NLP and LLM

    4m 11s
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    Quantifying the potential ROI of NLP and LLM projects

    3m 42s
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    Building a business case for NLP and LLM initiatives

    6m 35s
• 3. Ethical Considerations and Responsible AI 3. Ethical Considerations and Responsible AI

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    Bias and fairness in NLP and LLMs

    3m 43s
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    Privacy and data security

    5m 28s
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    Responsible AI practices

    5m 56s
• 4. Leading NLP and LLM Projects 4. Leading NLP and LLM Projects

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    Key roles in an NLP/LLM team

    4m 51s
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    Team essential skills and competencies

    2m 27s
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    Project management and execution

    4m 39s
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    Metrics for model deployment and evaluation

    4m 48s
• 5. Future Trends 5. Future Trends

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    The evolving landscape of NLP and LLMs

    6m 13s
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    Prepare for the future: Build a NLP/LLM strategy

    5m 39s
• Conclusion Conclusion

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    Next steps

    1m 9s