
Online or onsite, instructor-led live Large Language Models (LLMs) training courses demonstrate through interactive hands-on practice how to use Large Language Models for various natural language tasks.
LLMs training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Large Language Models (LLMs) trainings in Singapore can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg also offers bespoke Large Language Models (LLMs) consultancy services in Singapore. Our consultants have helped hundreds of clients around the world get unstuck. Our clients value our highly-personalized consulting approach and find consulting to be well-suited for complex long-term projects, short-term projects requiring niche expertise, urgent problem fixing, critical knowledge transfer, and team coaching and support. To learn more about our past consultancy engagements, see consultancy case studies.
If instead you need people for continuous projects, NobleProg can support your organisation with a full range of staff. Whether your needs are for medium-term or long-term assignments, entry-level or highly-skilled expertise, single-person or multi-person personnel, our interim staffing / staff augmentation solutions can provide you with the talent needed to complete your most challenging projects. Contact us for more information.
NobleProg -- Your Local Training Provider
Testimonials
I did like the exercises
Office for National Statistics
Course: Natural Language Processing with Python
Very knowledgeable
Usama Adam - TWPI
Course: Natural Language Processing with TensorFlow
The way he present everything with examples and training was so useful
Ibrahim Mohammedameen - TWPI
Course: Natural Language Processing with TensorFlow
Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject
Ali Kattan - TWPI
Course: Natural Language Processing with TensorFlow
This is one of the best quality online trainings I have ever taken in my 13 year career. Keep up the great work!
Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
This is one of the best hands-on with exercises programming courses I have ever taken.
Laura Kahn
Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
The topics referring to NLG. The team was able to learn something new in the end with topics that were interesting but it was only in the last day. There were also more hands on activities than slides which was good.
Accenture Inc
Course: Python for Natural Language Generation
the last day. generation part
Accenture Inc
Course: Python for Natural Language Generation
I like that it focuses more on the how-to of the different text summarization methods
Course: Text Summarization with Python
About face area.
中移物联网
Course: Deep Learning for NLP (Natural Language Processing)
This is one of the best quality online trainings I have ever taken in my 13 year career. Keep up the great work!
Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
I like that it focuses more on the how-to of the different text summarization methods
Course: Text Summarization with Python
Large Language Models Course Outlines in Singapore
- Explain what generative AI is and how it works.
- Describe the transformer architecture that powers LLMs.
- Use empirical scaling laws to optimize LLMs for different tasks and constraints.
- Apply state-of-the-art tools and methods to train, fine-tune, and deploy LLMs.
- Discuss the opportunities and risks of generative AI for society and business.
- Set up a development environment that includes a popular LLM.
- Create a basic LLM and fine-tune it on a custom dataset.
- Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
- Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.
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