LLMs for Automated Customer Support Training Course
Large Language Models (LLMs) represent a form of artificial intelligence capable of processing and generating human-like text, thereby enabling more natural and effective automated customer support.
This instructor-led, live training (available 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.
Format of the Course
- Interactive lecture and discussion.
- Abundant 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 Large Language Models (LLMs)
- Overview of AI in customer support
- Fundamentals of LLMs
- Evolution of chatbots: from simple scripts to AI-driven support
Architecture of LLMs
- Understanding the building blocks of LLMs
- Neural networks and deep learning in LLMs
- Training LLMs: data, algorithms, and computational resources
Implementing LLMs in Chatbots
- Integration strategies for LLMs in existing systems
- Designing conversational flows and user interactions
- Ensuring contextual understanding and coherence
Enhancing Chatbot Responsiveness
- Techniques for real-time response generation
- Handling concurrent conversations
- Personalization and predictive support
User Experience and Interface Design
- Crafting user-friendly chatbot interfaces
- Visual and textual cues for better engagement
- Feedback loops and continuous improvement
Ethical Considerations and Compliance
- Privacy and data security with LLMs
- Ethical use of AI in customer support
- Adhering to industry standards and regulations
Testing and Deployment
- Quality assurance and testing methodologies
- Deployment strategies for scalability and reliability
- Monitoring and maintenance of chatbot systems
Case Studies and Real-world Applications
- Analyzing successful implementations of LLM chatbots
- Lessons learned and best practices
- Future trends and innovations in AI-driven customer support
Project and Assessment
- Designing and building an LLM-based chatbot
- Peer reviews and group discussions
- Final assessment and feedback
Summary and Next Steps
Requirements
- An understanding of basic programming concepts
- Experience with Python programming is recommended but not required
- Familiarity with basic machine learning concepts is beneficial
Audience
- Customer support professionals
- IT professionals
- Business analysts
Open Training Courses require 5+ participants.
LLMs for Automated Customer Support Training Course - Booking
LLMs for Automated Customer Support Training Course - Enquiry
LLMs for Automated Customer Support - Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph 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.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework designed for building and running coding agents that can interact with codebases, developer tools, and APIs to enhance engineering productivity.
This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level ML engineers, developer-tooling teams, and SREs who wish 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.
- 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.
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 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.
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 for domain-specific performance.
- Implement versioning, monitoring, and lifecycle governance.
- Ensure security, compliance, and responsible usage of open-source models.
Format of the Course
- Interactive lecture and discussion.
- Hands-on exercises in self-hosting and fine-tuning.
- Live-lab implementation of governance and monitoring pipelines.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
LangGraph Applications in Finance
35 HoursLangGraph 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.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph 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.
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 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.
LangGraph for Legal Applications
35 HoursLangGraph 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.
Building Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph 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.
LangGraph for Marketing Automation
14 HoursLangGraph serves as a graph-based orchestration framework that facilitates conditional, multi-step workflows involving LLMs and tools, making it highly suitable for automating and personalizing content pipelines.
This instructor-led, live training (available online or onsite) is designed for intermediate-level marketers, content strategists, and automation developers seeking 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 incorporating conditional logic.
- Integrate LLMs, APIs, and data sources to enable 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 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 arrange.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursLe Chat Enterprise offers a private ChatOps solution that delivers secure, customizable, and governed conversational AI capabilities for organizations, featuring support for 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 who aim to deploy, configure, and govern Le Chat Enterprise within enterprise environments.
Upon completion of this training, participants will be capable of:
- Setting up and configuring Le Chat Enterprise for secure deployments.
- Enabling RBAC, SSO, and compliance-driven controls.
- Integrating Le Chat with enterprise applications and data stores.
- Designing and implementing governance and admin playbooks for ChatOps.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practice sessions.
- 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 family of high-performance large language models specifically optimized for cost-effective, large-scale production deployment.
This instructor-led training session, available either online or onsite, is designed for advanced infrastructure engineers, cloud architects, and MLOps leaders who aim to design, deploy, and optimize architectures based on Mistral to achieve maximum throughput while minimizing costs.
Upon completion of this training, participants will be capable of:
- Implementing scalable deployment patterns for Mistral Medium 3.
- Applying batching, quantization, and efficient serving techniques.
- Optimizing inference costs without compromising performance.
- Designing production-ready serving topologies tailored for enterprise workloads.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical applications.
- Hands-on implementation within a live laboratory environment.
Customization Options
- To request a customized training session for this course, please contact us to make arrangements.
Productizing Conversational Assistants with Mistral Connectors & Integrations
14 HoursMistral AI is an open-source artificial intelligence platform that empowers teams to develop and integrate conversational assistants into both enterprise internal operations and customer-facing workflows.
This instructor-led live training, available online or onsite, targets beginner to intermediate-level product managers, full-stack developers, and integration engineers looking to design, integrate, and productize conversational assistants using Mistral connectors and integrations.
Upon completion of this training, participants will be able to:
- Integrate Mistral conversational models with enterprise and SaaS connectors.
- Implement retrieval-augmented generation (RAG) to ensure grounded responses.
- Design user experience patterns for both internal and external chat assistants.
- Deploy assistants into product workflows to address real-world use cases.
Format of the Course
- Interactive lectures and discussions.
- Hands-on integration exercises.
- Live-lab development of conversational assistants.
Course Customization Options
- To request a customized training session 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 robust, production-grade deployment across enterprise environments.
This instructor-led live training, available either online or onsite, is designed for intermediate to advanced AI/ML engineers, platform architects, and MLOps professionals seeking to deploy, optimize, and secure Mistral Medium 3 for complex enterprise use cases.
Upon completion of this training, participants will be equipped to:
- Deploy Mistral Medium 3 via API services and self-hosted solutions.
- Optimize inference performance while managing costs.
- Implement diverse multimodal use cases leveraging Mistral Medium 3.
- Apply security and compliance best practices tailored for enterprise settings.
Course Format
- Interactive lectures and group discussions.
- Extensive exercises and practical practice.
- Hands-on implementation within a live laboratory environment.
Customization Options
- To request a tailored training experience for this course, please contact us to arrange details.
Mistral for Responsible AI: Privacy, Data Residency & Enterprise Controls
14 HoursMistral AI is an open, enterprise-ready AI platform designed to support secure, compliant, and responsible AI deployments.
This instructor-led training, available both online and onsite, targets intermediate-level compliance leads, security architects, and legal or operations stakeholders who aim to implement responsible AI practices using Mistral. The course focuses on leveraging privacy, data residency, and enterprise control mechanisms.
Upon completion, participants will be able to:
- Deploy privacy-preserving techniques within Mistral environments.
- Implement data residency strategies to satisfy regulatory obligations.
- Establish enterprise-grade controls, including RBAC, SSO, and audit logging.
- Assess vendor and deployment options to ensure alignment with compliance standards.
Course Format
- Interactive lectures and discussions.
- Case studies and exercises focused on compliance.
- Hands-on implementation of enterprise AI controls.
Customization Options
- To arrange customized training for this course, please contact us.
Multimodal Applications with Mistral Models (Vision, OCR, & Document Understanding)
14 HoursMistral models represent open-source AI technologies that are expanding into multimodal workflows, effectively supporting both language and vision tasks for enterprise and research applications.
This instructor-led live training, available either online or onsite, targets intermediate-level machine learning researchers, applied engineers, and product teams aiming to develop multimodal applications using Mistral models, including OCR and document understanding pipelines.
Upon completion of this training, participants will be equipped to:
- Configure and set up Mistral models for multimodal tasks.
- Implement OCR workflows and seamlessly integrate them with NLP pipelines.
- Design document understanding applications tailored for enterprise use cases.
- Create vision-text search capabilities and assistive UI functionalities.
Course Format
- Interactive lectures and discussions.
- Practical coding exercises.
- Live-lab implementation of multimodal pipelines.
Customization Options
- To request customized training for this course, please contact us to make arrangements.