Deploying Tencent Hunyuan in Production: Low-Latency Inference & Cost Optimization Training Course
This practical program provides guidance on the reliable, large-scale production deployment of Tencent Hunyuan models, with a focus on reducing inference latency and optimizing expenditures.
Designed for intermediate-level engineers and architects, this instructor-led session—available in online or onsite formats—enables participants to deploy large and MoE models using Tencent Hunyuan, thereby achieving lower latency, enhanced GPU utilization, and managed operational costs tailored for government
Upon completion of this training, participants will be equipped to:
- identify key production challenges associated with serving Tencent Hunyuan models.
- implement practical inference optimization strategies, including TensorRT, KV-cache tuning, quantization, and batching.
- develop scalable deployment architectures utilizing autoscaling, monitoring, and capacity planning.
- balance latency and cost factors to support real-world production workloads.
Training Format
- Interactive lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation within a live-lab environment.
Course Customization Options
- To arrange customized training for this course, please contact us to coordinate your requirements.
Course Outline
Tencent Hunyuan Production Fundamentals
- Overview of Tencent Hunyuan model serving scenarios relevant to government applications
- Production characteristics of large and MoE models
- Common latency, throughput, and cost bottlenecks
- Defining service-level objectives for inference workloads in a federal context
Deployment Architecture and Serving Flow
- Core components of a production inference stack suitable for government use cases
- Choosing between containerized, on-premise, and cloud deployment models that align with agency security policies
- Model loading, request routing, and GPU allocation basics
- Designing for reliability and operational simplicity to support continuous service delivery
Latency Optimization in Practice
- Using optimized inference engines such as TensorRT where applicable to enhance performance
- KV-cache concepts and practical cache tuning
- Reducing startup, warmup, and response overhead to meet time-sensitive operational needs
- Measuring time to first token and token generation speed for effective workload evaluation
Throughput, Batching, and GPU Efficiency
- Continuous batching and request batching strategies to maximize resource utilization
- Managing concurrency and queue behavior to ensure equitable service access
- Improving GPU utilization without harming user experience for internal stakeholders
- Handling long-context and mixed-workload requests typical of complex government data processing
Quantization and Cost Control
- Why quantization matters for production serving in resource-constrained environments
- Practical trade-offs of FP16, INT8, and other common precision options for compliance and efficiency
- Balancing model quality, latency, and infrastructure cost to ensure fiscal responsibility
- Building a simple cost optimization checklist for sustainable technology management
Operations, Monitoring, and Readiness Review
- Autoscaling triggers for inference services to maintain service level agreements
- Monitoring latency, throughput, cache usage, and GPU health to ensure system integrity
- Logging, alerting, and incident response basics aligned with federal cybersecurity standards
- Reviewing a reference deployment and creating an improvement plan to enhance operational readiness for government missions
Requirements
- Fundamental comprehension of deployment and inference procedures associated with large language models
- Practical experience utilizing containerization, cloud or on-premises infrastructure, and API-driven services within a government context for government applications
- Proficiency in Python programming or general systems engineering responsibilities
Audience
- Mechanical engineers tasked with operationalizing large language models in production environments
- Platform engineers managing GPU-accelerated inference services
- Solution architects developing scalable AI serving architectures
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
Deploying Tencent Hunyuan in Production: Low-Latency Inference & Cost Optimization Training Course - Booking
Deploying Tencent Hunyuan in Production: Low-Latency Inference & Cost Optimization Training Course - Enquiry
Deploying Tencent Hunyuan in Production: Low-Latency Inference & Cost Optimization - Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph provides a framework for developing stateful, multi-agent large language model (LLM) applications through composable graphs that maintain persistent state and precise execution control.
This instructor-led training, available online or onsite, targets advanced AI platform engineers, DevOps specialists for AI systems, and machine learning architects seeking to optimize, debug, monitor, and manage production-grade LangGraph environments. The curriculum is specifically designed for government
- 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.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework engineered to facilitate the creation and execution of coding agents capable of interacting with code repositories, development tools, and application programming interfaces (APIs) to improve engineering efficiency.
This instructor-led live training, available online or on-site, targets intermediate to advanced machine learning engineers, developer tooling teams, and Site Reliability Engineers (SREs) seeking to design, implement, and optimize coding agents using Devstral for government applications.
Upon completion of this training, participants will be able to:
- Establish and configure Devstral for coding agent development.
- Design agentic workflows for codebase exploration and modification.
- Integrate coding agents with developer tools and APIs.
- Implement best practices for secure and efficient agent deployment.
Course Format
- Interactive lecture and discussion.
- Extensive exercises and practice.
- Hands-on implementation in a live-lab environment.
Customization Options
- To request a customized training for this course, please contact us to arrange.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral represent open-source artificial intelligence frameworks engineered for adaptable deployment, targeted fine-tuning, and scalable system integration.
This instructor-led instructional program, available via online or onsite delivery, targets intermediate to advanced machine learning engineers, platform operations teams, and research specialists seeking to self-host, fine-tune, and manage the governance of Mistral and Devstral models within operational production environments for government applications.
Upon completion of this curriculum, participants will be equipped to:
- Deploy and configure self-hosted infrastructure for Mistral and Devstral architectures.
- Execute fine-tuning methodologies to optimize domain-specific performance metrics.
- Establish robust version control, monitoring protocols, and lifecycle governance frameworks.
- Assure security standards, regulatory compliance, and responsible utilization of open-source models.
Course Format
- Engaging lectures and structured discussion panels.
- Practical laboratory exercises focused on self-hosting and fine-tuning processes.
- Real-time implementation of governance and monitoring pipelines within a live lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
LangGraph Applications in Finance
35 HoursLangGraph provides a structured framework for developing state-preserving, multi-agent LLM applications as composable graphs, enabling persistent state management and precise control over execution flows.
This instructor-led live training, available in online or onsite formats, is designed for intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based financial solutions with adherence to governance, observability, and compliance standards. This program delivers essential capabilities for government and public sector entities requiring robust, secure AI infrastructure.
Upon completion of this training, participants will be equipped to:
- Develop finance-specific LangGraph workflows that align with regulatory mandates and audit requirements.
- Integrate financial data standards and ontologies into graph state architectures and tooling ecosystems.
- Establish reliability, safety protocols, and human-in-the-loop controls for critical operational processes.
- Deploy, monitor, and optimize LangGraph systems to ensure performance, cost-efficiency, and service level agreement (SLA) compliance.
Course Format
- Interactive lecture and group discussion.
- Extensive exercises and practical application.
- Hands-on implementation within a live laboratory environment.
Customization Options
- To request a customized training program tailored to specific agency needs, please contact us for arrangement.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph provides a framework for developing graph-based large language model applications that facilitate planning, branching, tool integration, memory management, and controlled execution.
This instructor-led, live training program, available in online or onsite formats, targets entry-level developers, prompt engineers, and data practitioners seeking to design and implement reliable, multi-step LLM workflows using LangGraph. This curriculum is specifically structured for government
Upon completion of this training, participants will be able to:
- Articulate fundamental LangGraph principles, including nodes, edges, and state, and identify appropriate use cases.
- Construct prompt chains capable of branching logic, tool invocation, and memory retention.
- Incorporate retrieval mechanisms and external application programming interfaces into graph-based workflows.
- Test, debug, and evaluate LangGraph applications to ensure reliability and safety.
Course Format
- Interactive lectures accompanied by facilitated discussions.
- Guided laboratory exercises and code walkthroughs within a sandbox environment.
- Scenario-based training focused on design, testing, and evaluation methodologies.
Customization Options
- To request customized training for this course, please contact us to arrange.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph facilitates stateful, multi-agent workflows driven by large language models, offering precise governance over execution pathways and data persistence. Within the healthcare sector, these technical capabilities are essential for ensuring regulatory compliance, system interoperability, and the development of clinical decision-support tools that integrate seamlessly with established medical protocols.
This instructor-led training, available in online or onsite formats, targets intermediate to advanced professionals seeking to architect, deploy, and govern LangGraph-based healthcare solutions. The curriculum addresses critical regulatory, ethical, and operational complexities inherent in public health infrastructure.
Upon completion of this program, participants will be equipped to:
- Architect healthcare-specific LangGraph workflows that prioritize compliance documentation and audit trails.
- Integrate LangGraph applications with medical ontologies and industry standards, including FHIR, SNOMED CT, and ICD.
- Implement best practices for system reliability, traceability, and explainability within sensitive operational environments.
- Deploy, monitor, and validate LangGraph applications in healthcare production settings to ensure consistent performance.
Instructional Format
- Interactive lectures and structured discussions.
- Practical exercises utilizing real-world case studies.
- Implementation practice within a live-lab environment tailored for government.
Course Customization Options
- For agencies requiring customized training aligned with specific mandates, please contact the program office to arrange bespoke sessions.
LangGraph for Legal Applications
35 HoursLangGraph is an open-source framework designed for constructing stateful, multi-agent large language model applications through composable graphs that maintain persistent state and offer precise execution control.
This instructor-led training program, available in online or onsite formats, targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions with rigorous compliance, traceability, and governance standards. The curriculum is specifically structured for government agencies requiring robust technical oversight and accountability mechanisms for AI-driven workflows.
Upon completion of this training, participants will be equipped to:
- Design legal-specific LangGraph workflows that ensure auditability and regulatory compliance.
- Integrate legal ontologies and document standards into graph state management and processing logic.
- Implement protective guardrails, human-in-the-loop approval processes, and traceable decision pathways.
- Deploy, monitor, and maintain LangGraph services in production environments with enhanced observability and cost controls.
Course Format
- Interactive lectures and structured discussions.
- Extensive practical exercises and skill-building activities.
- Hands-on implementation within a live laboratory environment.
Customization Options
- To request a customized training configuration for this course, please contact our team to arrange scheduling and specific requirements.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph provides a framework for constructing graph-structured workflows with large language models (LLMs) that facilitate branching logic, tool integration, memory management, and controlled execution flows.
This instructor-led live training, available online or onsite, targets intermediate-level engineers and product teams seeking to integrate LangGraph’s graph-based logic with LLM agent cycles. The curriculum supports the development of dynamic, context-aware applications, including customer service agents, decision trees, and information retrieval systems.
Upon completion of this course, participants will be equipped to:
- Design graph-driven workflows that coordinate LLM agents, external tools, and memory components.
- Implement conditional routing, retry mechanisms, and fallback protocols to ensure robust execution.
- Integrate retrieval systems, APIs, and structured outputs into agent cycles.
- Evaluate, monitor, and secure agent behavior to enhance reliability and safety standards.
Format of the Course
- Interactive lectures and facilitated discussions.
- Guided labs and code walkthroughs within a sandbox environment.
- Scenario-based design exercises and peer reviews.
Course Customization Options
- To request customized training tailored for government or enterprise requirements, please contact us to arrange.
LangGraph for Marketing Automation
14 HoursLangGraph serves as a graph-based orchestration framework that facilitates conditional, multi-step workflows involving large language models (LLMs) and external tools, making it well-suited for automating and tailoring content production pipelines.
This instructor-led, live training session, available in online or onsite formats, targets intermediate-level marketing professionals, content strategists, and automation developers seeking to deploy dynamic, branching email campaigns and content generation systems using LangGraph. The curriculum is specifically designed for government applications.
Upon completion of this instruction, participants will demonstrate the ability to:
- Construct graph-structured workflows for content and email distribution that incorporate conditional logic.
- Integrate LLMs, application programming interfaces (APIs), and data repositories to enable automated personalization.
- Oversee state management, memory retention, and contextual continuity across complex, multi-step campaigns.
- Assess, monitor, and optimize workflow efficiency and delivery metrics.
Course Delivery Structure
- Interactive lectures coupled with collaborative group discussions.
- Practical laboratory exercises focused on implementing email workflows and content pipelines.
- Scenario-based training addressing personalization strategies, audience segmentation, and branching logic.
Training Customization Availability
- To arrange customized training for this course, please contact the program administrators to coordinate your requirements.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursLe Chat Enterprise constitutes a secured, governable ChatOps framework that delivers adaptable conversational artificial intelligence to federal and civilian agencies. The platform supports role-based access control (RBAC), single sign-on (SSO), standardized connectors, and integration with established enterprise applications for government entities.
This instructor-led training, available via secure online channels or at designated federal facilities, targets intermediate professionals including product managers, IT leadership, solution engineers, and compliance officers responsible for deploying and governing Le Chat Enterprise within complex organizational infrastructures.
Upon completion of this instructional course, participants will be equipped to:
- Configure Le Chat Enterprise to meet rigorous security standards for government deployments.
- Implement RBAC, SSO, and compliance-driven access controls.
- Facilitate integration between Le Chat and existing enterprise applications and federal data repositories.
- Develop and operationalize governance and administrative procedures for government ChatOps operations.
Instructional Methodology
- Interactive instruction accompanied by technical discussion.
- Extensive practical exercises and scenario-based learning.
- Direct implementation experience within a live-lab environment designed for government training.
Curriculum Adaptation
- Agencies requiring specialized curriculum adjustments should contact the training coordination team to establish arrangements.
Cost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursMistral comprises a high-performance family of large language models designed to enable cost-effective production deployment at scale.
This instructor-led live training, available online or onsite, targets advanced-level infrastructure engineers, cloud architects, and MLOps leads seeking to design, deploy, and optimize Mistral-based architectures for maximum throughput and minimum cost, including solutions specifically tailored for government.
Upon completion of this training, participants will be able to:
- Implement scalable deployment patterns for Mistral Medium 3.
- Apply batching, quantization, and efficient serving strategies.
- Optimize inference costs while maintaining performance.
- Design production-ready serving topologies for enterprise workloads.
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.
Productizing Conversational Assistants with Mistral Connectors & Integrations
14 HoursMistral AI operates as an open-source artificial intelligence platform, empowering teams to construct and embed conversational assistants within enterprise operations and customer engagement workflows.
This instructor-led session, available in online or onsite formats, targets product managers, full-stack developers, and integration engineers with beginner to intermediate proficiency. The curriculum focuses on designing, integrating, and operationalizing conversational assistants utilizing Mistral connectors and integration frameworks for government solutions.
Upon completion of this training, participants will be capable of:
- Connecting Mistral conversational models to enterprise and SaaS connectors.
- Implementing retrieval-augmented generation (RAG) to ensure accurate and grounded responses.
- Architecting user experience patterns for both internal and external chat interfaces.
- Deploying assistants into product workflows to address real-world operational requirements.
Course Format
- Interactive lectures and discussions.
- Practical integration exercises.
- Real-time lab development of conversational assistants.
Customization Options
- To request customized training for this course, please contact us to arrange.
Enterprise-Grade Deployments with Mistral Medium 3
14 HoursMistral Medium 3 is a high-performance, multimodal large language model engineered for production-grade deployment within enterprise settings. It offers robust capabilities for government agencies seeking advanced AI integration.
This instructor-led, live training (available online or onsite) targets intermediate to advanced-level AI/ML engineers, platform architects, and MLOps teams who need to deploy, optimize, and secure Mistral Medium 3 for critical government applications.
Upon completion of this training, participants will be able to:
- Deploy Mistral Medium 3 using API or self-hosted options to meet federal infrastructure requirements.
- Optimize inference performance and manage costs effectively.
- Implement multimodal use cases leveraging Mistral Medium 3 for diverse mission needs.
- Apply security and compliance best practices essential for enterprise and government environments.
Format of the Course
- Interactive lecture and discussion to facilitate knowledge transfer.
- Extensive exercises and practice scenarios.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange the session.
Mistral for Responsible AI: Privacy, Data Residency & Enterprise Controls
14 HoursMistral AI operates as an open-source and enterprise-capable artificial intelligence platform designed to facilitate secure, compliant, and responsible AI initiatives.
This instructor-led instructional session, available in online or on-site formats, is directed at intermediate-level compliance officers, security architects, and legal or operations stakeholders seeking to integrate responsible AI frameworks into Mistral environments through the utilization of privacy protections, data residency protocols, and enterprise governance mechanisms for government applications.
Upon completion of this training, participants will be equipped to:
- Deploy privacy-preserving methodologies within Mistral infrastructure.
- Execute data residency strategies that satisfy regulatory mandates.
- Establish enterprise-grade controls, including Role-Based Access Control (RBAC), Single Sign-On (SSO), and audit logging capabilities.
- Assess vendor and deployment alternatives to ensure alignment with compliance standards.
Course Delivery Format
- Interactive lectures and facilitated discussions.
- Case studies and exercises focused on compliance requirements.
- Practical implementation of enterprise AI controls.
Customization Options
- For information regarding customized training for this course, please contact the provider to make arrangements.
Multimodal Applications with Mistral Models (Vision, OCR, & Document Understanding)
14 HoursMistral models constitute open-source artificial intelligence infrastructure that now supports multimodal operational workflows, enabling both natural language processing and computer vision capabilities for enterprise and research initiatives.
This instructor-led training program, available via online or onsite delivery, targets intermediate-level machine learning researchers, applied engineering staff, and product development teams seeking to develop multimodal applications using Mistral models, specifically including optical character recognition (OCR) and document comprehension pipelines designed for government contexts.
Upon completion of this instruction, participants will be able to:
- Deploy and configure Mistral models for multimodal operational tasks.
- Execute OCR workflows and integrate them with natural language processing systems.
- Architect document understanding applications tailored for enterprise requirements.
- Create vision-text search capabilities and assistive user interface functionalities.
Course Structure
- Interactive lectures and professional discussions.
- Practical coding exercises.
- Live laboratory implementation of multimodal pipelines.
Customization Opportunities
- To request a customized training curriculum for this course, please contact the administration to arrange arrangements.
