LLMs for Cybersecurity Training Course
Cybersecurity is a dynamic and constantly changing field, with new threats emerging every day. Large Language Models (LLMs) provide innovative solutions for detecting threats and implementing security measures.
This instructor-led, live training (available online or onsite) is designed for intermediate-level cybersecurity professionals and data scientists who want to leverage LLMs to improve cybersecurity protocols and threat intelligence.
By the end of this training, participants will be able to:
- Understand the role of LLMs in cybersecurity.
- Implement LLMs for threat detection and analysis.
- Utilize LLMs for security automation and response.
- Integrate LLMs with existing security infrastructure.
Format of the Course
- 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.
Course Outline
Introduction to Cybersecurity and LLMs
- Current landscape of cybersecurity threats
- Basics of Large Language Models
- Advantages of using LLMs in cybersecurity
LLMs for Threat Detection
- Using LLMs to analyze and interpret security logs
- Training LLMs for anomaly and pattern detection
- Case studies: LLMs in intrusion detection systems
LLMs for Security Automation
- Automating incident response with LLMs
- LLMs in phishing detection and email filtering
- Enhancing security protocols with AI
LLMs for Threat Intelligence
- Gathering and processing threat intelligence with LLMs
- LLMs for predictive threat modeling
- Sharing and disseminating intelligence with LLMs
Integrating LLMs into Security Operations
- Best practices for deploying LLMs in security operations centers
- Maintaining and updating LLMs for optimal performance
- Addressing privacy and ethical concerns
Hands-on Lab: Implementing LLMs in Cybersecurity
- Setting up a cybersecurity lab environment with LLMs
- Developing a threat detection model using LLMs
- Simulating attacks and testing model effectiveness
Summary and Next Steps
Requirements
- An understanding of cybersecurity fundamentals
- Experience with Python programming
- Familiarity with machine learning concepts
Audience
- Cybersecurity professionals
- Data scientists
- IT professionals interested in the latest AI-driven security technologies
Open Training Courses require 5+ participants.
LLMs for Cybersecurity Training Course - Booking
LLMs for Cybersecurity Training Course - Enquiry
LLMs for Cybersecurity - Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph is a framework designed for constructing stateful, multi-agent LLM applications as composable graphs featuring persistent state and precise execution control.
This instructor-led live training, available either online or on-site, is tailored for advanced AI platform engineers, DevOps professionals specializing in AI, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.
Upon completion of this training, participants will be able to:
- Design and optimize intricate LangGraph topologies to enhance speed, reduce costs, and ensure scalability.
- Enhance reliability through retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
- Debug and trace graph executions, inspect states, and systematically reproduce issues encountered in production.
- Instrument graphs with logs, metrics, and traces; deploy them to production; and monitor SLAs and associated costs.
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.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework built for creating and operating 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 looking to design, implement, and optimize coding agents using Devstral.
By the end 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.
Format of the Course
- 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) targets intermediate to advanced ML 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 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 processes.
- Ensure security, compliance, and responsible usage of open-source models.
Format of the Course
- Interactive lectures and discussions.
- Hands-on exercises focused on self-hosting and fine-tuning.
- Live-lab implementation of governance and monitoring pipelines.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework for constructing stateful, multi-actor LLM applications by composing graphs that maintain persistent state and allow precise control over execution flow.
This instructor-led live training, available either online or onsite, targets intermediate to advanced professionals seeking to design, implement, and manage finance solutions based on LangGraph, ensuring proper governance, observability, and regulatory compliance.
Upon completion of this training, participants will be capable of:
- Designing LangGraph workflows tailored to financial regulations and audit requirements.
- Integrating financial data standards and ontologies into graph states and tools.
- Implementing reliability, safety measures, and human-in-the-loop controls for critical processes.
- Deploying, monitoring, and optimizing LangGraph systems to meet performance, cost, and SLA targets.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical sessions.
- Hands-on implementation within a live-lab environment.
Customization Options
- For requests regarding customized training for this course, please contact us to make arrangements.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph is a framework designed for constructing graph-structured Large Language Model (LLM) applications that support planning, branching, tool use, memory, and controllable execution.
This instructor-led, live training (available online or on-site) targets beginner-level developers, prompt engineers, and data practitioners who want to design and build reliable, multi-step LLM workflows using LangGraph.
By the conclusion of this training, participants will be able to:
- Explain core LangGraph concepts (nodes, edges, state) and understand when to apply them.
- Build prompt chains that branch, invoke tools, and maintain memory.
- Integrate retrieval mechanisms and external APIs into graph workflows.
- Test, debug, and evaluate LangGraph applications to ensure reliability and safety.
Format of the Course
- Interactive lectures and facilitated discussions.
- Guided labs and code walkthroughs within a sandbox environment.
- Scenario-based exercises focusing on design, testing, and evaluation.
Course Customization Options
- To request customized training for this course, please contact us to arrange.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph empowers stateful, multi-agent 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 seamlessly align with clinical workflows.
This instructor-led live training, available online or on-site, is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.
Upon completion of this training, participants will be equipped to:
- Design healthcare-specific LangGraph workflows prioritizing compliance and auditability.
- Integrate LangGraph applications with established medical ontologies and standards, including FHIR, SNOMED CT, and ICD.
- Apply industry best practices for reliability, traceability, and explainability within sensitive environments.
- Deploy, monitor, and validate LangGraph applications in production healthcare settings.
Course Format
- Interactive lectures and discussions.
- Hands-on exercises featuring real-world case studies.
- Implementation practice within a live laboratory environment.
Customization Options
- To request a customized version of this course, please contact us to arrange details.
LangGraph for Legal Applications
35 HoursLangGraph serves as a framework designed for constructing stateful, multi-agent LLM applications through composable graphs that maintain persistent state and offer precise execution control.
This instructor-led live training, available both online and onsite, targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based legal solutions equipped with essential compliance, traceability, and governance controls.
Upon completion of this training, participants will be capable of:
- Crafting legal-specific LangGraph workflows that ensure auditability and compliance.
- Integrating legal ontologies and document standards into graph state and processing mechanisms.
- Implementing guardrails, human-in-the-loop approvals, and traceable decision pathways.
- Deploying, monitoring, and maintaining LangGraph services in production environments with robust observability and cost management.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live lab environment.
Customization Options for the Course
- To request customized training for this course, please get in touch with us to arrange details.
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.
Course Format
- Interactive lecture and facilitated discussion.
- Guided labs and code walkthroughs in a sandbox environment.
- Scenario-based design exercises and peer reviews.
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 supports conditional, multi-step workflows involving LLMs and tools, making it ideal for automating and personalizing content pipelines.
This instructor-led live training (available online or onsite) targets intermediate-level marketers, content strategists, and automation developers looking to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.
By the end 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.
Format of the Course
- 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 offers a secure, customizable, and governed conversational AI platform designed for organizational use, featuring support for RBAC, SSO, connectors, and enterprise application integrations.
This instructor-led training (available online or onsite) targets intermediate-level product managers, IT leads, solution engineers, and security/compliance professionals looking to deploy, configure, and manage Le Chat Enterprise in enterprise settings.
Upon completion, participants will be able to:
- Deploy and configure Le Chat Enterprise securely.
- Implement RBAC, SSO, and compliance-driven controls.
- Connect Le Chat with enterprise applications and data repositories.
- Design and enforce governance and administrative guidelines for ChatOps.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice.
- Hands-on implementation in a live-lab environment.
Customization Options
- Contact us to arrange customized training for this course.
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 AI platform that enables teams to build and integrate conversational assistants into enterprise and customer-facing workflows.
This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level 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 offers an open and enterprise-ready AI platform designed to support secure, compliant, and responsible AI deployments.
This instructor-led live training, available both online and on-site, targets compliance leaders, security architects, and legal/operations stakeholders at an intermediate level. The course focuses on implementing responsible AI practices using Mistral by leveraging privacy safeguards, data residency options, and enterprise control mechanisms.
Upon completing this training, participants will be able to:
- Deploy privacy-preserving techniques within Mistral environments.
- Utilize data residency strategies to satisfy regulatory mandates.
- Configure enterprise-grade controls including RBAC, SSO, and audit logging.
- Assess vendor and deployment choices to ensure compliance alignment.
Course Format
- Interactive lectures and discussions.
- Case studies and exercises focused on compliance.
- Practical implementation of enterprise AI controls.
Customization Options
- For customized training arrangements, please contact us directly.
Multimodal Applications with Mistral Models (Vision, OCR, & Document Understanding)
14 HoursMistral models are open-source artificial intelligence technologies that have expanded into multimodal workflows, supporting both language and vision tasks for enterprise and research applications.
This instructor-led, live training (available online or onsite) is designed for intermediate-level ML researchers, applied engineers, and product teams who aim to create multimodal applications using Mistral models, including OCR and document understanding pipelines.
Upon completion 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.
Course Format
- Interactive lecture and discussion.
- Hands-on coding exercises.
- Live-lab implementation of multimodal pipelines.
Customization Options
- To request a customized training for this course, please contact us to arrange.