Building Secure and Responsible LLM Applications Training Course
Security for LLM applications involves the design, construction, and maintenance of systems that are safe, reliable, and adhere to established policies when leveraging large language models.
This instructor-led, live training (available online or on-site) is designed for AI developers, architects, and product managers at an intermediate to advanced level who aim to identify and mitigate risks linked to LLM-powered applications. Key risks include prompt injection, data leakage, and unfiltered outputs, while addressing these through security controls such as input validation, human-in-the-loop oversight, and output guardrails.
Upon completion of this training, participants will be capable of:
- Gaining insight into the primary vulnerabilities inherent in LLM-based systems.
- Implementing secure design principles within LLM application architecture.
- Utilizing tools like Guardrails AI and LangChain for validation, filtering, and ensuring safety.
- Incorporating techniques such as sandboxing, red teaming, and human-in-the-loop reviews into production-grade pipelines.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical application.
- Hands-on implementation within a live laboratory environment.
Customization Options for the Course
- To arrange customized training for this course, please contact us to make the necessary arrangements.
Course Outline
Overview of LLM Architecture and Attack Surface
- How LLMs are built, deployed, and accessed via APIs.
- Key components in LLM app stacks (e.g., prompts, agents, memory, APIs).
- Where and how security issues arise in real-world use.
Prompt Injection and Jailbreak Attacks
- What is prompt injection and why it’s dangerous.
- Direct and indirect prompt injection scenarios.
- Jailbreaking techniques to bypass safety filters.
- Detection and mitigation strategies.
Data Leakage and Privacy Risks
- Accidental data exposure through responses.
- PII leaks and model memory misuse.
- Designing privacy-conscious prompts and retrieval-augmented generation (RAG).
LLM Output Filtering and Guarding
- Using Guardrails AI for content filtering and validation.
- Defining output schemas and constraints.
- Monitoring and logging unsafe outputs.
Human-in-the-Loop and Workflow Approaches
- Where and when to introduce human oversight.
- Approval queues, scoring thresholds, fallback handling.
- Trust calibration and role of explainability.
Secure LLM App Design Patterns
- Least privilege and sandboxing for API calls and agents.
- Rate limiting, throttling, and abuse detection.
- Robust chaining with LangChain and prompt isolation.
Compliance, Logging, and Governance
- Ensuring auditability of LLM outputs.
- Maintaining traceability and prompt/version control.
- Aligning with internal security policies and regulatory needs.
Summary and Next Steps
Requirements
- Fundamental understanding of large language models and prompt-based interfaces.
- Practical experience in building LLM applications using Python.
- Familiarity with API integrations and cloud-based deployments.
Target Audience
- AI developers.
- Application and solution architects.
- Technical product managers working with LLM tools.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
Contact us for an exact quote and to hear our latest promotions
(*The final price may vary depending on the technical specialization of the course, the level of customization, the method of delivery and the number of learners)
Need help picking the right course?
opleidingen@nobleprog.com or +31 208 080 666
Building Secure and Responsible LLM Applications Training Course - Enquiry
Building Secure and Responsible LLM Applications - Consultancy Enquiry
Provisional Upcoming Courses (Contact Us For More Information)
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursThis instructor-led live training (available online or onsite) targets advanced AI platform engineers, DevOps professionals specializing in AI, and ML architects who aim to optimize, debug, monitor, and operate production-grade LangGraph systems.
Upon completion of this course, participants will be able to:
- Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
- Ensure reliability through strategies such as retries, timeouts, idempotency, and checkpoint-based recovery.
- Debug and trace graph executions, inspect state data, and systematically reproduce production issues.
- Instrument graphs with logs, metrics, and traces, deploy to production environments, and monitor SLAs and costs effectively.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation in a live-lab environment.
Customization Options
- To request customized training for this course, please contact us to arrange your session.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework built for creating and executing coding agents capable of interacting with codebases, developer utilities, 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 who aim to design, implement, and optimize coding agents using Devstral.
Upon completion of 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 lecture and discussion.
- Extensive 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.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral are open-source AI technologies engineered for flexible deployment, fine-tuning, and scalable integration.
This instructor-led live training, available online or onsite, is designed for intermediate to advanced machine learning engineers, platform teams, and research engineers who aim to self-host, fine-tune, and govern Mistral and Devstral models within production environments.
Upon completion of this training, participants will be equipped to:
- Establish and configure self-hosted environments for Mistral and Devstral models.
- Apply fine-tuning techniques to optimize performance for specific domains.
- Implement versioning, monitoring, and lifecycle governance strategies.
- 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 customized training for this course, please contact us to arrange details.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework for constructing stateful, multi-agent LLM applications through composable graphs, enabling persistent state management and precise execution control.
This instructor-led, live training session, available either online or onsite, is designed for intermediate to advanced professionals looking to design, implement, and manage LangGraph-based financial solutions with a focus on proper governance, observability, and compliance.
Upon completion of this training, participants will be equipped to:
- Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
- Integrate financial data standards and ontologies into graph state and supporting tools.
- Implement reliability, safety, and human-in-the-loop controls for critical processes.
- Deploy, monitor, and optimize LangGraph systems to meet performance, cost, and SLA targets.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical applications.
- Hands-on implementation within a live laboratory environment.
Customization Options
- To request a tailored version of this course, please contact us to arrange.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework designed for creating graph-structured applications leveraging Large Language Models (LLMs), enabling features such as planning, branching, tool integration, memory management, and controlled execution.
This instructor-led live training, available either online or onsite, is tailored for developers at the beginner level, prompt engineers, and data professionals looking to design and construct reliable, multi-step LLM workflows using LangGraph.
Upon completing this training, participants will be equipped to:
- Articulate core LangGraph concepts (nodes, edges, state) and determine appropriate use cases.
- Construct prompt chains capable of branching, invoking tools, and maintaining context memory.
- Incorporate retrieval mechanisms and external APIs into graph-based workflows.
- Test, debug, and evaluate LangGraph applications to ensure reliability and safety.
Course Format
- Interactive lectures combined with facilitated discussions.
- Guided laboratory sessions and code walkthroughs conducted within a sandbox environment.
- Scenario-based exercises focusing on design, testing, and evaluation.
Course Customization Options
- To arrange customized training for this course, please contact us directly.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph facilitates stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are vital for ensuring compliance, interoperability, and building decision-support systems that align with medical workflows.
This instructor-led live training (available online or onsite) targets intermediate to advanced-level professionals who aim to design, implement, and manage LangGraph-based healthcare solutions while addressing 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 customized training for this course, please contact us to arrange.
LangGraph for Legal Applications
35 HoursLangGraph is a framework designed for building stateful, multi-actor LLM applications as composable graphs with persistent state and precise control over execution.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and operate LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.
By the end of this training, participants will be able to:
- Design legal-specific LangGraph workflows that preserve auditability and compliance.
- Integrate legal ontologies and document standards into graph state and processing.
- Implement guardrails, human-in-the-loop approvals, and traceable decision paths.
- Deploy, monitor, and maintain LangGraph services in production with observability and cost controls.
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 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 serves as a graph-based orchestration framework, facilitating conditional, multi-step workflows involving Large Language Models (LLMs) and external tools. It is particularly well-suited for automating and personalizing content pipelines.
This instructor-led live training, available both online and onsite, targets intermediate-level marketers, content strategists, and automation developers. The course focuses on implementing dynamic, branching email campaigns and content generation pipelines using LangGraph.
Upon completion of this training, participants will be equipped to:
- Design graph-structured workflows for emails and content, incorporating conditional logic.
- Integrate LLMs, APIs, and various data sources to enable automated personalization.
- Effectively manage state, memory, and context across complex, multi-step campaigns.
- Evaluate, monitor, and optimize the performance and delivery outcomes of workflows.
Format of the Course
- Interactive lectures combined with group discussions.
- Hands-on labs focused on implementing email workflows and content pipelines.
- Scenario-based exercises covering personalization, segmentation, and branching logic.
Course Customization Options
- To request a customized training for this course, please contact us to make arrangements.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursLe Chat Enterprise offers a confidential ChatOps solution, delivering secure, customizable, and governed conversational AI capabilities tailored for organizational needs. It supports RBAC, SSO, connectors, and enterprise app integrations.
This instructor-led live training (available online or onsite) targets intermediate-level product managers, IT leads, solution engineers, and security/compliance teams looking to deploy, configure, and govern Le Chat Enterprise within enterprise environments.
Upon completion of this training, participants will be equipped to:
- Set up and configure Le Chat Enterprise for secure deployments.
- Activate RBAC, SSO, and compliance-driven controls.
- Integrate Le Chat with enterprise applications and data stores.
- Design and implement governance and admin playbooks for ChatOps.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical work.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
Cost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursMistral is a high-performance family of large language models optimized for cost-effective production deployment at scale.
This instructor-led, live training (online or onsite) is aimed at advanced-level infrastructure engineers, cloud architects, and MLOps leads who wish to design, deploy, and optimize Mistral-based architectures for maximum throughput and minimum cost.
By the end 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 is an open-source 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 product managers, full-stack developers, and integration engineers who wish to design, integrate, and productize conversational assistants using Mistral connectors and integrations.
By the end of this training, participants will be able to:
- Integrate Mistral conversational models with enterprise and SaaS connectors.
- Implement retrieval-augmented generation (RAG) for grounded responses.
- Design UX patterns for internal and external chat assistants.
- Deploy 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 serves as an open, enterprise-ready platform designed to facilitate secure, compliant, and responsible AI deployment through its robust feature set.
This instructor-led live training, available both online and on-site, targets intermediate-level professionals including compliance leads, security architects, and legal/operations stakeholders seeking to embed responsible AI practices within their organizations. Participants will learn to leverage privacy safeguards, data residency protocols, and enterprise control mechanisms provided by Mistral.
Upon completing this training, participants will be able to:
- Deploy privacy-preserving techniques within Mistral environments.
- Execute data residency strategies that align with regulatory mandates.
- Configure enterprise-grade controls, including Role-Based Access Control (RBAC), Single Sign-On (SSO), and comprehensive audit logging.
- Evaluate various vendor and deployment models to ensure alignment with compliance objectives.
Course Format
- Interactive lectures and group discussions.
- Compliance-focused case studies and practical exercises.
- Hands-on implementation of enterprise AI security controls.
Customization Options
- To request a customized version of this course, please contact us to arrange the details.
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.
