Whether delivered online or onsite, instructor-led live Large Language Models (LLMs) training courses demonstrate through interactive, hands-on practice how to utilize Large Language Models for various natural language tasks.
LLMs training is available as "online live training" or "onsite live training". Online live training (also known as "remote live training") is conducted via an interactive remote desktop. Onsite live training can be delivered locally at customer premises in Milan or at NobleProg corporate training centers in Milan.
NobleProg also provides bespoke Large Language Models (LLMs) consultancy services in Milan. Our consultants have assisted hundreds of clients worldwide in overcoming challenges. Clients value our highly personalized consulting approach, finding it particularly well-suited for complex long-term projects, short-term projects requiring niche expertise, urgent problem resolution, critical knowledge transfer, and team coaching and support. To learn more about our past consultancy engagements, please review our case studies.
If you require personnel for ongoing projects, NobleProg can support your organization with a comprehensive range of staff. Whether you need resources for medium-term or long-term assignments, entry-level or highly specialized expertise, or single or multi-person teams, our interim staffing and staff augmentation solutions can provide the talent needed to complete your most challenging projects. Contact us for more information.
NobleProg -- Your Local Training Provider
Milan
NobleProg Milan, Via Scarlatti 4, Milan, italy, 20124
The meeting center is close to central part of the city and near the central station. It is easy to rech the place with the underground. In that neighbourhood there are many shops and restaurants.
This instructor-led, live training in Milan (online or onsite) is designed for senior management professionals who want to grasp the fundamentals of LLMs, explore their potential impact on business operations, and evaluate practical applications of AI tools like ChatGPT, Microsoft Copilot, or Grok for real-world tasks such as content creation, data summarization, and decision support.
By the end of this training, participants will be able to:
Understand the concept of LLMs and how tools like ChatGPT and Copilot operate.
Apply prompting techniques to achieve practical and reliable results from LLMs.
Evaluate real-world use cases, including email drafting, document summarization, and productivity automation.
Identify investment opportunities and strategic applications for AI adoption.
This instructor-led, live training in Milan (online or onsite) is designed for senior management teams seeking to understand the strategic value of LLMs and enterprise AI tools. Participants will explore methods to integrate these tools into high-level workflows, draft more effective prompts, and evaluate opportunities for increasing productivity and ROI through AI adoption.
Upon completing this training, participants will be able to:
Comprehend how LLMs function and how tools like ChatGPT and Copilot leverage them.
Use prompt-based interactions to automate and accelerate tasks.
Apply AI tools to real-world scenarios such as email drafting, report summarization, and agreement review.
Evaluate the strategic benefits, limitations, and licensing considerations for LLM adoption.
This instructor-led, live training in Milan (online or onsite) is aimed at intermediate-level to advanced-level AI researchers, data scientists, and developers who wish to understand, fine-tune, and implement Meta AI's Large Language Models for various NLP applications.
By the end of this training, participants will be able to:
Understand the architecture and functioning of Meta AI's Large Language Models.
Set up and fine-tune Meta AI LLMs for specific use cases.
Implement LLM-based applications such as text summarization, chatbots, and sentiment analysis.
Optimize and deploy large language models efficiently.
This instructor-led, live training in Milan (online or onsite) is designed for intermediate-level AI professionals, business analysts, and technology leaders who seek to understand the fundamentals of generative AI and its business applications for LLMs. Participants will cover transformers, prompt engineering, and ethical considerations involved in deploying these models for real-world solutions.
Upon completion of this training, participants will be capable of:
Grasping the core principles behind generative AI and large language models.
Implementing and fine-tuning LLMs for targeted business use cases.
Utilizing prompt engineering techniques to achieve optimal model outputs.
Identifying ethical considerations and mitigating risks during LLM deployment.
Delivered as an instructor-led, live training session in Milan (online or onsite), this program targets intermediate-level AI professionals and ethicists, data scientists and engineers, as well as policy makers and stakeholders who seek to understand and navigate the ethical landscape surrounding LLMs.
Upon completion of this training, participants will be equipped to:
Identify ethical issues and challenges associated with LLMs.
Apply ethical frameworks and principles to LLM deployment.
Assess the societal impact of LLMs and mitigate potential risks.
Develop strategies for responsible AI development and usage.
This instructor-led, live training in Milan (online or onsite) is designed for intermediate-level NLP practitioners, data scientists, content creators, translators, and global enterprises seeking to utilize LLMs for language translation and multilingual content production.
Upon completing this training, participants will be able to:
Grasp the fundamentals of cross-lingual learning and translation using LLMs.
Deploy LLMs to translate content between various languages.
Create and manage multilingual datasets for training LLMs.
Formulate strategies to ensure consistency and high quality in translations.
This instructor-led, live training in Milan (online or onsite) is tailored for intermediate-level financial analysts, data scientists, and investment professionals who wish to leverage LLMs for financial market analysis and prediction.
By the end of this training, participants will be able to:
Understand the application of LLMs in financial market analysis.
Use LLMs to process financial news, reports, and data for market insights.
Develop predictive models for stock prices, market trends, and economic indicators.
Integrate LLM insights into investment decision-making processes.
This instructor-led, live training in Milan (online or onsite) is designed for intermediate-level environmental scientists, researchers, data analysts, and policymakers and advocates who wish to apply LLMs to environmental modeling and analysis.
By the end of this training, participants will be able to:
Understand the application of LLMs in environmental science.
Utilize LLMs to analyze and model environmental data.
Interpret LLM outputs for environmental impact assessments.
Communicate findings effectively to inform policy and conservation efforts.
This instructor-led, live training in Milan (online or onsite) is aimed at intermediate-level VR and AR developers, game designers, and AI engineers who wish to incorporate LLMs into VR and AR applications to create more engaging and responsive environments.
By the end of this training, participants will be able to:
Understand the role of LLMs in creating immersive VR and AR experiences.
Develop VR and AR applications that utilize LLMs for interactive dialogues and content creation.
Integrate LLMs with VR and AR development tools for enhanced user engagement.
Apply best practices for designing AI-driven narratives and interactions in virtual spaces.
This instructor-led, live training in Milan (online or onsite) targets intermediate-level data scientists, machine learning engineers, and software developers interested in applying Large Language Models (LLMs) to multimodal data for advanced AI applications.
By the conclusion of this training, participants will be able to:
Understand the principles of multimodal learning with LLMs.
Implement LLMs to process and analyze text, image, and audio data.
Develop applications that leverage the strengths of multimodal data integration.
Evaluate the performance of multimodal LLM systems.
This instructor-led, live training in Milan (online or on-site) targets intermediate-level cybersecurity professionals and data scientists aiming to leverage LLMs to strengthen cybersecurity measures and threat intelligence.
Upon completion of this training, participants will be capable of:
Understanding the role of LLMs in cybersecurity.
Implementing LLMs for threat detection and analysis.
Utilizing LLMs for security automation and response.
Integrating LLMs with existing security infrastructure.
This instructor-led, live training in Milan (online or onsite) is designed for intermediate-level data scientists and business analysts who aim to use large language models (LLMs) to forecast trends and behaviors across various industries.
By the end of this training, participants will be able to:
Understand the fundamentals of LLMs and their role in predictive analytics.
Implement LLMs to analyze and forecast data in various industries.
Evaluate the effectiveness of predictive models using LLMs.
Integrate LLMs with existing data processing pipelines.
This instructor-led, live training in Milan (online or onsite) targets 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 Milan (online or onsite) is designed for intermediate-level content creators, marketers, and educational technologists who want to leverage LLMs to produce high-quality, diverse, and engaging content across various fields.
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 Milan (online or onsite) is designed for educators, EdTech professionals, and researchers of varying experience levels who wish to leverage LLMs to create 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 Milan (online or on-site) is targeted at intermediate-level ML practitioners and AI developers who wish to fine-tune and deploy open-weight models such as LLaMA, Mistral, and Qwen for specific business or internal applications.
By the end of this training, participants will be able to:
Understand the ecosystem and differences between open-source LLMs.
Prepare datasets and fine-tuning configurations for models like LLaMA, Mistral, and Qwen.
Execute fine-tuning pipelines using Hugging Face Transformers and PEFT.
Evaluate, save, and deploy fine-tuned models in secure environments.
This instructor-led, live training in Milan (online or onsite) is designed for beginner to intermediate 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 Milan (online or onsite) targets customer support and IT professionals at beginner to intermediate levels who aim to implement LLMs to develop responsive and intelligent customer support chatbots.
Upon completion of this training, participants will be able to:
Grasp the fundamentals and architecture of Large Language Models (LLMs).
Design and integrate LLMs into customer support systems.
Improve 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 Milan (online or in-person) targets intermediate-level data scientists and AI engineers who want to fine-tune large language models more affordably and efficiently using methods like LoRA, Adapter Tuning, and Prefix Tuning.
By the end of this training, participants will be able to:
Understand the theory behind parameter-efficient fine-tuning approaches.
Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
Compare performance and cost trade-offs of PEFT methods vs. full fine-tuning.
Deploy and scale fine-tuned LLMs with reduced compute and storage requirements.
This instructor-led, live training in Milan (online or onsite) targets intermediate to advanced machine learning engineers, AI developers, and data scientists who want to learn how to utilize QLoRA for the efficient fine-tuning of large models tailored to specific tasks.
By the end of this training, participants will be able to:
Understand the theory behind QLoRA and quantization techniques for LLMs.
Implement QLoRA in fine-tuning large language models for domain-specific applications.
Optimize fine-tuning performance on limited computational resources using quantization.
Deploy and evaluate fine-tuned models in real-world applications efficiently.
This instructor-led, live training in Milan (available online or onsite) is designed for 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 Milan (online or onsite) is designed for intermediate-level software developers and technical writers who aim to harness LLMs to optimize their coding workflows and produce detailed, comprehensive documentation.
Upon completion of this training, participants will be able to:
Grasp the role of LLMs in automating code generation and software documentation.
Employ LLMs to generate accurate and efficient code snippets and documentation.
Integrate LLMs into their software development lifecycle to boost productivity.
Uphold high-quality documentation standards using automated tools.
Address ethical considerations and best practices for utilizing AI in software development.
This instructor-led, live training in Milan (online or onsite) is designed for intermediate-level business professionals and data analysts seeking to harness the power of LLMs to extract business insights.
Upon completing this training, participants will be able to:
Comprehend the foundational concepts and practical applications of LLMs within business intelligence.
Utilize LLMs to analyze extensive datasets and derive meaningful insights.
Integrate LLM-powered analytics into strategic business decision-making processes.
Assess ethical considerations and best practices for employing LLMs in business environments.
Anticipate emerging AI trends and prepare for the evolving business intelligence landscape.
This instructor-led, live training in Milan (online or onsite) targets intermediate to advanced 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:
Install 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 Milan (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 Milan (online or onsite) targets intermediate-level professionals who aim to leverage prompt engineering and few-shot learning to optimize LLM performance for real-world applications.
Upon completing this training, participants will be capable of:
Grasping the core principles of prompt engineering and few-shot learning.
Creating effective prompts tailored for various NLP tasks.
Applying few-shot techniques to adapt LLMs with minimal data.
Optimizing LLM performance for practical use cases.
LangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs that maintain persistent state and offer precise control over execution.
This instructor-led live training, available online or onsite, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based legal solutions with robust compliance, traceability, and governance controls.
Upon completion of this training, participants will be capable of:
Developing legal-specific LangGraph workflows that ensure auditability and compliance.
Integrating legal ontologies and document standards into graph state and processing.
Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
Deploying, monitoring, and maintaining LangGraph services in production environments with observability and cost management.
Course Format
Interactive lectures and discussions.
Extensive exercises and practice sessions.
Hands-on implementation within a live lab environment.
Customization Options
For customized training on this course, please contact us to arrange your session.
This instructor-led, live training (available online or onsite) is designed for advanced-level engineers, AI specialists, and localization leads who wish to implement large language model (LLM) systems for automated translation, quality evaluation, and enterprise governance.
Upon completion of this training, participants will be able to:
Construct enterprise-grade LLM localization pipelines that integrate both open-source and proprietary models.
Implement automated QA workflows and quality metrics to ensure translation consistency.
Establish governance and approval frameworks for multilingual content production.
Deploy scalable, auditable LLM-based localization systems within secure environments.
AI for SQL involves applying artificial intelligence and Large Language Models (LLMs) to automate, optimize, and improve how SQL queries are generated, executed, and interpreted within enterprise data environments.
This instructor-led live training, available online or on-site, is designed for intermediate-level data engineers and technical leads looking to integrate AI capabilities into their SQL workflows. The goal is to enable natural language querying, intelligent optimization, and automated data analysis.
Upon completing this training, participants will be able to:
Integrate LLMs, including GPT, DeepSeek, LLaMA, Qwen, and Mistral, into SQL environments.
Develop natural-language-to-SQL pipelines for conversational data access.
Implement AI-driven query optimization and error detection mechanisms.
Design secure and auditable AI-SQL workflows suitable for enterprise use.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical practice.
Hands-on implementation within a live laboratory environment.
Customization Options
To request customized training for this course, please contact us to arrange.
LangGraph serves as a framework enabling the creation of stateful, multi-actor LLM applications through composable graphs that feature persistent state and precise execution control.
This instructor-led training session, available both online and onsite, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance standards.
Upon completion of this training, participants will gain the ability to:
Create LangGraph workflows tailored to finance that align with regulatory and audit requirements.
Incorporate financial data standards and ontologies into graph state and associated tooling.
Establish reliability, safety, and human-in-the-loop controls for critical processes.
Deploy, monitor, and optimize LangGraph systems to enhance performance, manage costs, and meet SLAs.
Course Format
Interactive lectures and discussions.
Extensive exercises and practice sessions.
Practical implementation in a live-lab environment.
Customization Options
To arrange customized training for this course, please contact us.
Vertex AI offers robust tools for constructing multimodal LLM workflows that seamlessly integrate text, audio, and image data into a unified pipeline. Featuring support for long context windows and Gemini API parameters, it facilitates advanced applications in planning, reasoning, and cross-modal intelligence.
This instructor-led live training, available online or on-site, is designed for intermediate to advanced practitioners looking to design, build, and optimize multimodal AI workflows within Vertex AI.
Upon completion of this training, participants will be able to:
Utilize Gemini models for handling multimodal inputs and outputs.
Develop long-context workflows to tackle complex reasoning tasks.
Create pipelines that combine text, audio, and image analysis.
Optimize Gemini API parameters to enhance performance and cost efficiency.
Course Format
Interactive lectures and discussions.
Practical labs focused on multimodal workflows.
Project-based exercises applying multimodal use cases.
Customization Options
For customized training requests, please contact us to arrange your session.
LangGraph facilitates stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these features are essential for ensuring compliance, interoperability, and the development of decision-support systems that align with medical workflows.
This instructor-led live training (available online or onsite) is designed for intermediate to advanced-level professionals who wish to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.
Upon completion of this training, participants will be able to:
Design healthcare-specific LangGraph workflows with compliance and auditability in mind.
Integrate LangGraph applications with medical ontologies and standards (FHIR, SNOMED CT, ICD).
Apply best practices for reliability, traceability, and explainability in sensitive environments.
Deploy, monitor, and validate LangGraph applications in healthcare production settings.
Format of the Course
Interactive lecture and discussion.
Hands-on exercises with real-world case studies.
Implementation practice in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led live training (available online or onsite) is designed for intermediate AI developers and localization engineers who want to build scalable, automated translation pipelines using proprietary and open-source LLMs.
By the end of this training, participants will be able to:
Design and deploy translation workflows using modern LLM frameworks and APIs.
Integrate open-source and commercial models into scalable translation systems.
Optimize translation quality through fine-tuning, prompt engineering, and automation.
Implement cost-efficient and compliant translation infrastructure for enterprise environments.
LangGraph is a framework designed for building stateful, multi-actor LLM applications as composable graphs with persistent state and control over execution.
This instructor-led, live training (online or onsite) is aimed at advanced-level AI platform engineers, DevOps for AI, and ML architects who wish to optimize, debug, monitor, and operate production-grade LangGraph systems.
By the end of this training, participants will be able to:
Design and optimize complex LangGraph topologies for speed, cost, and scalability.
Engineer reliability with retries, timeouts, idempotency, and checkpoint-based recovery.
Debug and trace graph executions, inspect state, and systematically reproduce production issues.
Instrument graphs with logs, metrics, and traces, deploy to production, and monitor SLAs and costs.
Format of the Course
Interactive lecture and discussion.
Lots of exercises and practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
This instructor-led, live training session in Milan (online or onsite) is tailored for 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.
Large language models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming how DevOps teams automate activities like change tracking, test generation, and alert triage by mimicking human-like collaboration and decision-making.
This instructor-led live training (available online or onsite) targets advanced engineers looking to design and implement DevOps automation workflows driven by large language models (LLMs) and multi-agent systems.
Upon completing this training, participants will be able to:
Integrate LLM-based agents into CI/CD workflows for intelligent automation.
Automate test generation, commit analysis, and change summaries using agents.
Coordinate multiple agents to triage alerts, generate responses, and provide DevOps recommendations.
Develop secure and maintainable agent-powered workflows using open-source frameworks.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical practice.
Hands-on implementation in a live-lab environment.
Course Customization Options
To arrange customized training for this course, please contact us.
Postgres serves as a robust, open-source relational database, providing a solid foundation for building AI-powered systems and data intelligence applications.
This instructor-led live training, available either online or onsite, is designed for intermediate-level database professionals and developers looking to integrate, manage, and optimize AI capabilities directly within Postgres.
Upon completing this training, participants will be able to:
Configure and set up Postgres extensions tailored for AI workloads.
Implement embeddings and perform similarity searches using pgvector.
Connect both open-source and proprietary LLMs to Postgres to derive real-time insights.
Optimize Postgres performance for AI-driven queries and workflows.
Course Format
Engaging lectures and interactive discussions.
Extensive exercises and practical practice sessions.
Hands-on implementation within a live-lab environment.
Customization Options
For personalized training arrangements, please contact us to discuss your needs.
This instructor-led, live training in Milan (online or onsite) targets intermediate to advanced AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while incorporating security controls like input validation, human-in-the-loop oversight, and output guardrails.
By the end of this training, participants will be able to:
Understand the core vulnerabilities of LLM-based systems.
Apply secure design principles to LLM app architecture.
Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.
This instructor-led, live training in Milan (online or onsite) is designed for intermediate to advanced professionals who want to customize pre-trained models for specific tasks and datasets.
By the end of this training, participants will be able to:
Grasp the principles of fine-tuning and its applications.
Prepare datasets for fine-tuning pre-trained models.
Fine-tune large language models (LLMs) for NLP tasks.
Optimize model performance and address common challenges.
LangGraph serves as a framework for composing graph-structured workflows powered by large language models (LLMs), featuring support for branching, tool integration, memory management, and controllable execution.
This instructor-led live training, available online or onsite, is designed for intermediate-level engineers and product teams aiming to merge LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications. Examples include customer support agents, decision trees, and information retrieval systems.
Upon completion of this training, participants will be capable of:
Designing graph-based workflows that coordinate LLM agents, tools, and memory.
Implementing conditional routing, retries, and fallback mechanisms for robust execution.
Integrating retrieval systems, APIs, and structured outputs into agent loops.
Evaluating, monitoring, and securing agent behavior to ensure reliability and safety.
Course Format
Interactive lectures and facilitated discussions.
Guided labs and code walkthroughs within a sandbox environment.
Scenario-based design exercises and peer reviews.
Customization Options
To request customized training for this course, please contact us to arrange.
This technical course focuses on applying Large Language Models (LLMs) to enhance code quality, minimize technical debt, and automate documentation tasks within software engineering teams.
Delivered as instructor-led live training, available either online or onsite, it is designed for software professionals with intermediate to advanced skill levels who aim to utilize LLMs, such as GPT, to analyze, refactor, and document complex or legacy codebases more effectively.
Upon completion of this training, participants will be able to:
Utilize LLMs to clarify code functionality, dependencies, and logic within unfamiliar repositories.
Identify and refactor anti-patterns to enhance code readability.
Automate the generation and maintenance of in-line comments, README files, and API documentation.
Integrate LLM-driven insights into existing CI/CD pipelines and code review workflows.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical application.
Hands-on implementation within a live-lab environment.
Course Customization Options
To request customized training for this course, please contact us to arrange.
This instructor-led, live training in Milan (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.
LangGraph serves as a framework for developing graph-structured applications powered by Large Language Models (LLMs), enabling features such as planning, branching, tool utilization, memory management, and controlled execution.
This instructor-led live training, available both online and onsite, is designed for developers at the beginner level, prompt engineers, and data professionals who aim to design and construct reliable, multi-step LLM workflows using LangGraph.
Upon completion of this training, participants will be equipped to:
Articulate core LangGraph concepts—including nodes, edges, and state—and understand when to apply them.
Construct prompt chains that support branching, tool invocation, and memory retention.
Integrate retrieval mechanisms and external APIs into graph-based workflows.
Test, debug, and evaluate LangGraph applications to ensure reliability and safety.
Course Format
Interactive lectures paired with facilitated discussions.
Guided laboratory sessions and code walkthroughs conducted within a sandbox environment.
Scenario-based exercises focusing on design, testing, and evaluation.
Customization Options
For those interested in customizing this training, please reach out to us to make arrangements.
This instructor-led, live training in Milan (online or onsite) is designed for beginner to intermediate-level developers who wish to apply Large Language Models to 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 Milan (online or onsite) targets intermediate-level engineers and architects who wish to use Tencent Hunyuan to deploy large and MoE models with reduced latency, higher throughput, and enhanced cost control.
By the end of this training, participants will be able to explain Hunyuan production deployment patterns, optimize inference performance, implement batching and quantization strategies, and plan scalable serving operations.
This instructor-led, live training in Milan (online or onsite) is tailored for intermediate-level developers, technical product teams, and AI practitioners who aim to use Hunyuan models to create multimodal applications for the generation and delivery of images, 3D models, and video.
By the end of this training, participants will be able to: build prompt-based workflows, generate and evaluate multimodal assets, serve outputs through applications or APIs, and connect Hunyuan capabilities to enterprise product stacks.
This instructor-led, live training in Milan (online or onsite) is designed for AI professionals at beginner, intermediate, or advanced levels who wish to utilize MCP to connect AI assistants with external tools, data, and enterprise services.
By the end of this training, participants will be able to explain MCP concepts, identify key architecture components, set up a basic integration, and apply security best practices.
This instructor-led, live training in Milan (online or onsite) is aimed at intermediate-level enterprise architects who wish to use Model Context Protocol to design secure, scalable, and governable agent integration platforms for enterprise environments.
By the end of this training, participants will be able to: explain MCP architecture and enterprise patterns, design secure integration platforms, apply governance and access controls, and evaluate deployment and scaling options.
This instructor-led, live training in Milan (online or onsite) is designed for intermediate-level developers, architects, and platform engineers who wish to utilize MCP to build reliable servers and clients suitable for enterprise deployment and operations.
By the end of this training, participants will be able to: explain MCP architecture in practice, build production-ready integrations, deploy and monitor MCP services, and apply patterns for versioning, resilience, and support.
This instructor-led training, offered online or onsite, is designed for intermediate-level IT leaders, compliance professionals, security teams, and enterprise architects. Participants will utilize sovereign AI principles and governance practices to design AI environments that protect sensitive data, adhere to localization requirements, and minimize vendor lock-in.
By the end of this training, participants will be able to explain sovereign AI concepts, assess hosting and governance options, define controls for prompts and logs, and develop a practical adoption roadmap.
Read more...
Last Updated:
Testimonials (2)
The course was very useful, and the trainer was clear, well-prepared, and engaging. I liked the fact that it was very practical with labs and real use cases.
Overall, it was a valuable training experience.
Mattia Dettori - MFM INVESTMENT Ltd Italian branch
Course - LLM Engineering Bootcamp
Examples and links excel repository
Olga - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
Online Large Language Models training in Milan, LLMs training courses in Milan, Weekend LLMs (Large Language Models) courses in Milan, Evening LLMs training in Milan, LLMs (Large Language Models) instructor-led in Milan, LLMs (Large Language Models) instructor-led in Milan, LLMs private courses in Milan, LLMs (Large Language Models) trainer in Milan, LLMs (Large Language Models) on-site in Milan, LLMs one on one training in Milan, Online Large Language Models training in Milan, LLMs boot camp in Milan, LLMs classes in Milan, Weekend Large Language Models training in Milan, Large Language Models (LLMs) coaching in Milan, Large Language Models (LLMs) instructor in Milan, Evening Large Language Models courses in Milan
