Introduction to NLP and LLMs: Principles and Practical Applications

Gain a practical understanding of natural language processing (NLP) and large language models (LLMs), unlocking the exciting possibilities of these transformative technologies.

Syllabus

Introduction

Principles and practical applications of NLP and LLMs
What you should know

1. Introduction to NLP and LLMs

What is natural language processing (NLP)?
Why process text data?
Understanding large language models (LLMs)
Key elements of LLMs

2. NLP and LLMs Use Cases

Identifying opportunities for NLP and LLM
Quantifying the potential ROI of NLP and LLM projects
Building a business case for NLP and LLM initiatives

3. Ethical Considerations and Responsible AI

Bias and fairness in NLP and LLMs
Privacy and data security
Responsible AI practices

4. Leading NLP and LLM Projects

Key roles in an NLP/LLM team
Team essential skills and competencies
Project management and execution
Metrics for model deployment and evaluation

5. Future Trends

The evolving landscape of NLP and LLMs
Prepare for the future: Build a NLP/LLM strategy

Conclusion

Next steps

Taught by

Derek Jedamski

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