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 Radom 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 Radom. 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
Radom
Hotel Promenda, Bulwarowa 15, Radom, Poland, 26-600
The training room is located 5 kilometers from the city center and 8 kilometers from the Warsaw-Radom airport.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level data scientists who wish to gain a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).By the end of this training, participants will be able to:
Understand the components and functionality of transformer models.
Optimize and fine-tune LLMs for specific tasks and applications.
Understand the core principles and methodologies of reinforcement learning.
Learn how reinforcement learning techniques can enhance the performance of LLMs.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level content creators, marketers, and educational technologists who wish to harness the power of LLMs for generating high-quality, diverse, and engaging content across various domains.By the end of this training, participants will be able to:
Understand the capabilities of LLMs and their application in content generation.
Set up and use LLMs for generating various types of content.
Apply best practices for prompting and fine-tuning LLMs to produce desired outputs.
Evaluate the quality of AI-generated content and refine it for specific audiences.
Explore advanced techniques for creative and multi-modal content generation with LLMs.
This instructor-led, live training in Radom (online or onsite) is aimed at educators, EdTech professionals, and researchers with varying levels of experience and expertise who wish to leverage LLMs for creating personalized educational experiences.By the end of this training, participants will be able to:
Understand the architecture and capabilities of LLMs.
Identify opportunities for personalization in educational content using LLMs.
Design adaptive learning platforms that utilize LLMs for content personalization.
Implement LLM-driven strategies for enhancing student engagement and learning outcomes.
Evaluate the effectiveness of LLMs in educational settings and make data-driven decisions for
This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level to intermediate-level software developers and data scientists who wish to implement LLMs in speech recognition and synthesis systems.By the end of this training, participants will be able to:
Understand the role of LLMs in speech technologies.
Implement LLMs for accurate speech recognition and natural-sounding speech synthesis.
Integrate LLMs with speech recognition engines and speech synthesizers.
Evaluate and improve the performance of speech systems using LLMs.
Stay informed about current trends and future directions in speech technologies.
This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level to intermediate-level customer support and IT professionals who wish to implement LLMs to create responsive and intelligent customer support chatbots.By the end of this training, participants will be able to:
Understand the fundamentals and architecture of Large Language Models (LLMs).
Design and integrate LLMs into customer support systems.
Enhance the responsiveness and user experience of chatbots.
Address ethical considerations and ensure compliance with industry standards.
Deploy and maintain an LLM-based chatbot for real-world applications.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level data and marketing professionals who wish to apply LLMs to analyze and interpret public sentiment from various text sources such as social media posts, product reviews, and customer feedback.By the end of this training, participants will be able to:
Understand the principles of sentiment analysis and its application using LLMs.
Preprocess and prepare datasets for sentiment analysis.
Train and fine-tune LLMs to accurately reflect sentiment in text.
Analyze sentiment in real-time from social media and other text sources.
Integrate sentiment analysis findings into business strategies and decision-making processes.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level software developers and technical writers who wish to leverage LLMs to streamline their coding workflow and create detailed, comprehensive documentation.By the end of this training, participants will be able to:
Understand the role of LLMs in automating code generation and software documentation.
Utilize LLMs to create accurate and efficient code snippets and documentation.
Integrate LLMs into their software development lifecycle for enhanced productivity.
Maintain high-quality documentation standards using automated tools.
Address ethical considerations and best practices for using AI in software development.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level business professionals and data analysts who wish to harness the power of LLMs for extracting business insights.By the end of this training, participants will be able to:
Understand the fundamentals and applications of LLMs in the context of business intelligence.
Apply LLMs to analyze large datasets and extract meaningful insights.
Integrate LLM-driven analytics into strategic business decision-making processes.
Evaluate the ethical considerations and best practices for using LLMs in business.
Anticipate future trends in AI and prepare for the evolving landscape of business intelligence.
This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level to advanced-level developers and data scientists who wish to master LlamaIndex for developing innovative LLM-powered applications.By the end of this training, participants will be able to:
Set up and configure LlamaIndex for use with LLMs.
Index and query custom datasets using LlamaIndex to enhance LLM functionality.
Design and develop sophisticated applications that utilize LlamaIndex and LLMs.
Understand and apply best practices for working with LLMs and LlamaIndex.
Navigate the ethical considerations involved in deploying LLM-powered applications.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance the capabilities of AI models, making them more accurate and reliable for various applications.By the end of this training, participants will be able to:
Understand the principles and components of LlamaIndex.
Ingest and structure data for use with LLMs.
Implement context augmentation to improve AI model performance.
Integrate LlamaIndex into existing AI systems and workflows.
This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level to intermediate-level data analysts and business professionals who wish to perform complex data analysis tasks more intuitively across various industries using Google Gemini AI.By the end of this training, participants will be able to:
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level content creators who wish to utilize Google Gemini AI to enhance their content quality and efficiency.By the end of this training, participants will be able to:
Understand the role of AI in content creation.
Set up and use Google Gemini AI to generate and optimize content.
Apply text-to-text transformations to produce creative and original content.
Implement SEO strategies using AI-driven insights.
Analyze content performance and adapt strategies using Gemini AI.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level customer service professionals who wish to implement Google Gemini AI in their customer service operations.By the end of this training, participants will be able to:
Understand the impact of AI on customer service.
Set up Google Gemini AI to automate and personalize customer interactions.
Utilize text-to-text and image-to-text transformations to improve service efficiency.
Develop AI-driven strategies for real-time customer feedback analysis.
Explore advanced features to create a seamless customer service experience.
This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to integrate AI functionalities into their applications using Google Gemini AI.By the end of this training, participants will be able to:
Understand the fundamentals of large language models.
Set up and use Google Gemini AI for various AI tasks.
Implement text-to-text and image-to-text transformations.
Build basic AI-driven applications.
Explore advanced features and customization options in Google Gemini AI.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level developers who wish to learn how to use generative AI with LLMs for various tasks and domains.By the end of this training, participants will be able to:
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.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level data scientists, AI developers, and AI enthusiasts who wish to use LLMs to perform various NLP tasks and create novel and diverse content for different purposes.By the end of this training, participants will be able to:
Establish a development environment with LLMs and essential tools.
Expertly perform NLU and NLI tasks with LLMs.
Extract, infer, and utilize knowledge graphs effectively.
Generate and manage dialogues using LLMs for conversational applications.
Evaluate content quality and diversity generated by LLMs and generative AI.
Apply ethical principles, ensuring fairness and responsible use of LLMs.
This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level to intermediate-level developers and software engineers who wish to learn the core concepts and architecture of LangChain and gain the practical skills for building AI-powered applications.By the end of this training, participants will be able to:
Grasp the fundamental principles of LangChain.
Set up and configure the LangChain environment.
Understand the architecture and how LangChain interacts with large language models (LLMs).
This instructor-led, live training in Radom (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Large Language Models for various natural language tasks.
By the end of this training, participants will be able to:
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.
This instructor-led, live training in Radom (online or onsite) is aimed at intermediate-level developers and software engineers who wish to build AI-powered applications using the LangChain framework.By the end of this training, participants will be able to:
Understand the fundamentals of LangChain and its components.
Integrate LangChain with large language models (LLMs) like GPT-4.
Build modular AI applications using LangChain.
Troubleshoot common issues in LangChain applications.
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