UMD Smith Unveils Exclusive Workshop on Large Language Model (LLM) Training

  • Workshop titled “Large Language Model Training and Development” offered by UMD’s Smith School of Business.
  • Targets data scientists and engineers in government and healthcare sectors.
  • Scheduled every Friday from August 2nd to August 23rd, 2024, in Greater Washington.
  • Focuses on technical aspects of LLMs, emphasizing industry-specific precision, data security, compliance, and operational streamlining.
  • Incorporates real-time coding exercises, suitable for Python proficient individuals.
  • Aims to empower participants to develop customized LLMs, particularly beneficial in secure data environments.
  • Upon completion, participants gain proficiency in deploying customized LLMs and understanding LLM foundations and transformers for enhanced text comprehension.

Main AI News:

In an era where data scientists and engineers, particularly in government and healthcare sectors, are increasingly seeking to harness the power of large language models (LLMs) such as ChatGPT, the Office of Executive Education at the University of Maryland’s Robert H. Smith School of Business is set to launch a groundbreaking workshop.

Enrollment is now open for “Large Language Model Training and Development,” a pioneering program in executive education set to debut in Greater Washington. Held on UMD’s College Park campus, the workshop will take place from 9 a.m. to 2:30 p.m. every Friday, spanning August 2nd to August 23rd, 2024.

This workshop offers a comprehensive exploration of the technical underpinnings of large language models, aligning perfectly with the Smith School’s ethos of fostering innovation in AI,” explains Kunpeng Zhang, an instructor and Associate Professor of Information Systems.

Zhang highlights several advantages that participants can expect to gain from mastering LLM development:

  • Industry-specific Precision: Crafting AI models attuned to the nuanced terminology and regulatory frameworks of specific industries ensures heightened accuracy and reliability in outcomes.
  • Data Security and Compliance: By training models on internal data, organizations can uphold data security standards and regulatory compliance, safeguarding sensitive information.
  • Operational Streamlining: Tailoring AI solutions to optimize processes and augment decision-making processes caters to the unique operational demands of diverse environments.

For those adept in Python, this course offers a stimulating challenge through real-time coding exercises,” Zhang asserts. “It is particularly relevant for data scientists and engineers operating within secure data environments, where reliance on public-facing AI tools is limited. By empowering participants to develop their own solutions, this workshop equips them to navigate commercial settings without extensive computational infrastructure.”

Upon completion of the workshop, participants will not only be proficient in deploying customized LLMs within their organizations but will also possess a robust understanding of LLM foundations and transformers. They will be adept at implementing transformer-based LLMs and harnessing pre-trained and fine-tuned paradigms for enhanced text comprehension.

Conclusion:

UMD Smith’s workshop on Large Language Model (LLM) training reflects a growing demand for specialized AI skills in sectors like government and healthcare. By addressing technical nuances and emphasizing customization, it equips professionals to navigate complex data environments while ensuring data security and compliance. This initiative underscores the increasing importance of tailored AI solutions in optimizing operational processes and decision-making.

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