Hunyuan Multimodal Applications: Practical Labs for Image, 3D, and Video Training Course
Hunyuan Multimodal Applications offers a hands-on approach to developing enterprise-grade workflows for generating images, 3D models, and video content.
This live, instructor-led training, available either online or onsite, is designed for intermediate developers, technical product teams, and AI practitioners looking to leverage Hunyuan models. You will learn to create prompt-to-asset workflows, evaluate multimodal outputs, and seamlessly integrate these capabilities into business applications.
Upon completion of this training, participants will be able to:
- Articulate the core functionalities and typical use cases of Hunyuan for image, 3D, and video workflows.
- Construct practical generation pipelines, spanning from prompt engineering to output evaluation.
- Distribute multimodal outputs via straightforward applications or APIs.
- Integrate Hunyuan-generated assets into product development, content creation, and review processes.
Course Format
- Interactive lectures and group discussions.
- Guided exercises and practical application.
- Real-world implementation within a live lab environment.
Course Customization Options
- To request customized training for this course, please reach out to us to arrange your session.
Course Outline
Hunyuan Multimodal Foundations and Lab Setup
- Grasping the multimodal capabilities of Hunyuan for image, 3D, and video applications.
- Identifying relevant business scenarios for creative, product, and content teams.
- Setting up the lab environment, sample assets, and model access permissions.
- Executing initial generation tasks and reviewing the outputs.
Prompt Design and Workflow Patterns
- Structuring prompts to achieve consistent multimodal results.
- Utilizing text prompts, reference images, and basic input configurations.
- Selecting appropriate workflows for image, video, or 3D generation.
- Refining prompts based on output quality and business objectives.
Image Generation and Review Labs
- Producing marketing, product, and concept images from prompts.
- Refining visual style, composition, and content consistency.
- Evaluating outputs for utility, quality, and alignment with brand identity.
- Organizing image assets for approval and downstream usage.
Video Generation Labs
- Creating short video clips from prompts and prepared inputs.
- Controlling style, scene intent, and output variation.
- Evaluating videos for clarity, continuity, and practical applicability.
- Preparing video assets for demonstration or integration into content workflows.
3D Asset Creation Labs
- Generating foundational 3D assets from text or image inputs.
- Assessing geometry, texture quality, and asset usability.
- Exporting assets for visualization, prototyping, or content pipelines.
- Evaluating when 3D generation is more suitable compared to image or video workflows.
Integration, Governance, and Next Steps
- Distributing generated assets via simple applications, services, or APIs.
- Linking multimodal outputs to product, content, and review workflows.
- Implementing practical checks for quality, brand safety, copyright compliance, and responsible use.
- Planning pilot use cases and defining next steps for internal adoption.
Requirements
- Fundamental knowledge of AI and generative AI concepts.
- Experience with web applications, APIs, or standard developer tools.
- Basic proficiency in Python or scripting languages.
Audience
- Developers creating AI-powered product features.
- Technical product managers and solution architects.
- Innovation, media, and digital teams managing image, video, or 3D content.
Open Training Courses require 5+ participants.
Hunyuan Multimodal Applications: Practical Labs for Image, 3D, and Video Training Course - Booking
Hunyuan Multimodal Applications: Practical Labs for Image, 3D, and Video Training Course - Enquiry
Hunyuan Multimodal Applications: Practical Labs for Image, 3D, and Video - Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph is a framework designed for creating stateful, multi-actor LLM applications as composable graphs with persistent state and control over execution.
This instructor-led, live training (available 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.
- Ample 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 build and operate coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.
This instructor-led live training, available online or onsite, targets intermediate to advanced ML engineers, developer-tooling teams, and SREs eager to design, implement, and optimize coding agents using Devstral.
Upon completing this training, participants will be able to:
- Set up 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 lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation in a live lab environment.
Customization Options
- To request a customized version of this course, please reach out to us to arrange details.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral models are open-source AI technologies designed to support flexible deployment, fine-tuning, and scalable integration.
This instructor-led live training (available online or onsite) is designed for intermediate to advanced ML engineers, platform teams, and research engineers who want to self-host, fine-tune, and govern Mistral and Devstral models in production environments.
By the end of this training, participants will be able to:
- Set up and configure self-hosted environments for Mistral and Devstral models.
- Apply fine-tuning techniques to enhance domain-specific performance.
- Implement versioning, monitoring, and lifecycle governance.
- Ensure security, compliance, and responsible usage of open-source models.
Course Format
- Interactive lectures and discussions.
- Hands-on exercises focused on self-hosting and fine-tuning.
- Live-lab implementation of governance and monitoring pipelines.
Customization Options
- To request a customized training session for this course, please contact us to arrange it.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework designed for constructing stateful, multi-actor LLM applications through composable graphs, enabling persistent state management and precise control over execution flows.
This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals who aim to design, implement, and manage LangGraph-based financial solutions while ensuring proper governance, observability, and compliance.
Upon completing this training, participants will be equipped to:
- Develop finance-specific LangGraph workflows that adhere to regulatory and audit standards.
- Integrate financial data standards and ontologies into graph states and associated tooling.
- Implement robust reliability, safety measures, and human-in-the-loop controls for critical processes.
- Deploy, monitor, and optimize LangGraph systems to achieve desired performance, cost efficiency, and SLAs.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live lab environment.
Customization Options
- To arrange customized training for this course, please contact us directly.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework for building graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.
This instructor-led, live training (online or onsite) is aimed at beginner-level developers, prompt engineers, and data practitioners who wish to design and build reliable, multi-step LLM workflows using LangGraph.
By the end of this training, participants will be able to:
- Explain core LangGraph concepts (nodes, edges, state) and when to use them.
- Build prompt chains that branch, call tools, and maintain memory.
- Integrate retrieval and external APIs into graph workflows.
- Test, debug, and evaluate LangGraph apps for reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in a sandbox environment.
- Scenario-based exercises on design, testing, and evaluation.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph facilitates stateful, multi-actor workflows driven by large language models (LLMs), offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, enabling interoperability, and developing decision-support systems that integrate seamlessly with clinical processes.
This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.
Upon completing this training, participants will be able to:
- Design healthcare-specific LangGraph workflows that prioritize compliance and auditability.
- Integrate LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
- Apply best practices for reliability, traceability, and explainability in sensitive environments.
- Deploy, monitor, and validate LangGraph applications within 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.
LangGraph for Legal Applications
35 HoursLangGraph serves as a framework designed for constructing 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 legal solutions that meet strict compliance, traceability, and governance standards.
Upon completion of this training, participants will be capable of:
- Creating legal-specific LangGraph workflows that ensure auditability and regulatory compliance.
- Integrating legal ontologies and document standards into graph states and processing logic.
- Implementing guardrails, human-in-the-loop approvals, and traceable decision paths.
- Deploying, monitoring, and maintaining LangGraph services in production environments with robust observability and cost controls.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- Hands-on implementation within a live-lab environment.
Customization Options
- To request customized training for this course, please contact us to make arrangements.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph is a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.
This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.
By the end of this training, participants will be able to:
- Design graph-based workflows that coordinate LLM agents, tools, and memory.
- Implement conditional routing, retries, and fallbacks for robust execution.
- Integrate retrieval, APIs, and structured outputs into agent loops.
- Evaluate, monitor, and harden agent behavior for reliability and safety.
Format of the Course
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in a sandbox environment.
- Scenario-based design exercises and peer reviews.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph for Marketing Automation
14 HoursLangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.
This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.
Upon completion of this training, participants will be able to:
- Design graph-structured content and email workflows with conditional logic.
- Integrate LLMs, APIs, and data sources for automated personalization.
- Manage state, memory, and context across multi-step campaigns.
- Evaluate, monitor, and optimize workflow performance and delivery outcomes.
Course Format
- Interactive lectures and group discussions.
- Hands-on labs implementing email workflows and content pipelines.
- Scenario-based exercises on personalization, segmentation, and branching logic.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursLe Chat Enterprise is a secure, customizable, and governed conversational AI platform designed for organizations, offering robust support for RBAC, SSO, connectors, and enterprise app integrations.
This instructor-led training (available online or onsite) targets intermediate-level product managers, IT leads, solution engineers, and security/compliance teams seeking to deploy, configure, and manage Le Chat Enterprise within enterprise environments.
Upon completion of this training, participants will be able to:
- Deploy and configure Le Chat Enterprise for secure operations.
- Implement RBAC, SSO, and compliance-driven controls.
- Connect Le Chat with enterprise applications and data stores.
- Design and execute governance and administrative playbooks for ChatOps.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation in a live-lab environment.
Customization Options
- For customized training options, please contact us to arrange.
Cost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursMistral is a family of high-performance large language models specifically optimized for cost-efficient deployment at scale in production environments.
This instructor-led training (available online or onsite) targets advanced infrastructure engineers, cloud architects, and MLOps leaders who want to design, deploy, and optimize Mistral-based architectures to maximize throughput while minimizing costs.
Upon completing 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 without compromising performance.
- Design production-ready serving topologies for enterprise workloads.
Course Format
- Interactive lecture and discussion.
- Extensive exercises and practical practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
Productizing Conversational Assistants with Mistral Connectors & Integrations
14 HoursMistral AI serves as an open AI platform that empowers teams to build and integrate conversational assistants into enterprise and customer-facing workflows.
This instructor-led live training (available online or onsite) is designed for beginner to intermediate-level product managers, full-stack developers, and integration engineers who want to design, integrate, and productize conversational assistants using Mistral connectors and integrations.
Upon completing this training, participants will be capable of:
- Integrating Mistral conversational models with enterprise and SaaS connectors.
- Implementing retrieval-augmented generation (RAG) for grounded responses.
- Designing UX patterns for internal and external chat assistants.
- Deploying assistants into product workflows for real-world use cases.
Format of the Course
- Interactive lecture and discussion.
- Hands-on integration exercises.
- Live-lab development of conversational assistants.
Course Customization Options
- To request a 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 designed for production-grade deployment across enterprise environments.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level AI/ML engineers, platform architects, and MLOps teams who wish to deploy, optimize, and secure Mistral Medium 3 for enterprise use cases.
By the end of this training, participants will be able to:
- Deploy Mistral Medium 3 using API and self-hosted options.
- Optimize inference performance and costs.
- Implement multimodal use cases with Mistral Medium 3.
- Apply security and compliance best practices for enterprise environments.
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.
Mistral for Responsible AI: Privacy, Data Residency & Enterprise Controls
14 HoursMistral AI is an open, enterprise-ready AI platform designed to facilitate secure, compliant, and responsible AI deployment.
This instructor-led live training, available online or onsite, targets intermediate-level compliance leads, security architects, and legal/ops stakeholders seeking to implement responsible AI practices using Mistral’s privacy, data residency, and enterprise control mechanisms.
By the end of this training, participants will be able to:
- Implement privacy-preserving techniques in Mistral deployments.
- Apply data residency strategies to meet regulatory requirements.
- Set up enterprise-grade controls such as RBAC, SSO, and audit logs.
- Evaluate vendor and deployment options for compliance alignment.
Format of the Course
- Interactive lecture and discussion.
- Compliance-focused case studies and exercises.
- Hands-on implementation of enterprise AI controls.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Multimodal Applications with Mistral Models (Vision, OCR, & Document Understanding)
14 HoursMistral models are open-source AI technologies that now extend into multimodal workflows, supporting both language and vision tasks for enterprise and research applications.
This instructor-led, live training (online or onsite) is aimed at intermediate-level ML researchers, applied engineers, and product teams who wish to build multimodal applications with Mistral models, including OCR and document understanding pipelines.
By the end of this training, participants will be able to:
- Set up and configure Mistral models for multimodal tasks.
- Implement OCR workflows and integrate them with NLP pipelines.
- Design document understanding applications for enterprise use cases.
- Develop vision-text search and assistive UI functionalities.
Format of the Course
- Interactive lecture and discussion.
- Hands-on coding exercises.
- Live-lab implementation of multimodal pipelines.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
