Large Language Models (LLMs) and Reinforcement Learning (RL) Training Course
Large Language Models (LLMs) represent advanced neural network architectures engineered to comprehend and generate human-like text based on provided inputs. Reinforcement Learning (RL) is a subset of machine learning in which an agent learns to make optimal decisions by executing actions within an environment to maximize cumulative rewards.
This instructor-led, live training session (available online or onsite) is designed for intermediate-level data scientists seeking a comprehensive understanding and practical proficiency in both Large Language Models (LLMs) and Reinforcement Learning (RL).
Upon completion of this training, participants will be able to:
- Understand the structural components and operational functionality of transformer models.
- Optimize and fine-tune LLMs for specific tasks and applications.
- Master the core principles and methodologies of reinforcement learning.
- Apply reinforcement learning techniques to enhance the performance and reliability of LLMs for government use cases.
Course Format
- Interactive lectures and facilitated discussions.
- Extensive exercises and practice scenarios.
- Hands-on implementation in a live-lab environment.
Customization Options
- To request a customized training program aligned with specific agency requirements, please contact us to arrange scheduling and scope.
Course Outline
Introduction to Large Language Models (LLMs)
- Foundational overview of LLMs
- Core definitions and strategic importance
- Current applications in artificial intelligence
Transformer Architecture
- Technical mechanics of transformer systems
- Key structural components and capabilities
- Input embedding and positional encoding techniques
- Multi-head attention mechanisms
- Feed-forward neural network layers
- Normalization and residual connections
Transformer Model Variants
- Self-attention processing logic
- Encoder-decoder structural designs
- Positional embedding strategies
- BERT (Bidirectional Encoder Representations from Transformers)
- GPT (Generative Pretrained Transformer)
Performance Optimization and Common Limitations
- Context window management
- Mamba and state-space model implementations
- Flash attention algorithms
- Sparse transformer architectures
- Vision transformer applications
- The role of quantization in efficiency
Enhancing Transformer Capabilities
- Retrieval-augmented generation methods
- Mixture of models frameworks
- Tree of thoughts reasoning techniques
Fine-Tuning Methodologies
- Theoretical basis of low-rank adaptation
- Implementation of fine-tuning with QLora
Scaling Laws and Optimization in LLMs
- The critical role of scaling laws in LLM deployment
- Scaling data volume and model size
- Computational resource scaling
- Parameter efficiency strategies
Operational Optimization
- Correlations among model size, data volume, compute resources, and inference needs
- Strategies for optimizing LLM performance and efficiency
- Best practices and tools for training and fine-tuning LLMs
Training and Fine-Tuning LLMs
- Procedures and challenges in training LLMs from initial stages
- Data acquisition and maintenance protocols
- Requirements for large-scale data, CPU, and memory resources
- Addressing optimization challenges
- Overview of the open-source LLM ecosystem
Fundamentals of Reinforcement Learning (RL)
- Introduction to Reinforcement Learning principles
- Decision-making through positive reinforcement
- Definitions and core concepts
- Markov Decision Process (MDP) frameworks
- Dynamic programming applications
- Monte Carlo methods
- Temporal Difference Learning techniques
Deep Reinforcement Learning
- Deep Q-Networks (DQN) implementation
- Proximal Policy Optimization (PPO) strategies
- Key elements of Reinforcement Learning systems
Integration of LLMs and Reinforcement Learning
- Synergies between LLMs and Reinforcement Learning
- Application of RL in enhancing LLMs
- Reinforcement Learning with Human Feedback (RLHF)
- Alternative methodologies to RLHF
Case Studies and Practical Applications
- Real-world implementation examples
- Analysis of success stories and operational challenges
Advanced Topics
- Advanced technical techniques
- Advanced optimization methods
- Cutting-edge research and developments
Summary and Next Steps
Requirements
- Basic understanding of Machine Learning
Audience
- Data scientists
- Software engineers
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
Large Language Models (LLMs) and Reinforcement Learning (RL) Training Course - Booking
Large Language Models (LLMs) and Reinforcement Learning (RL) Training Course - Enquiry
Large Language Models (LLMs) and Reinforcement Learning (RL) - Consultancy Enquiry
Upcoming Courses
Related Courses
Advanced LangGraph: Optimization, Debugging, and Monitoring Complex Graphs
35 HoursLangGraph serves as a framework for developing stateful, multi-actor LLM applications structured as composable graphs, featuring persistent state management and precise control over execution flows.
This instructor-led, live training session (available online or on-site) is designed for advanced AI platform engineers, DevOps professionals specializing in AI, and ML architects seeking to optimize, troubleshoot, monitor, and manage production-grade LangGraph systems for government environments.
Upon completion of this training, participants will be equipped to:
- Design and refine complex LangGraph structures to enhance velocity, cost-efficiency, and scalability.
- Implement robust reliability standards through retry mechanisms, timeout controls, idempotency, and checkpoint-based recovery.
- Diagnose and trace graph executions, inspect internal states, and methodically replicate production anomalies.
- Instrument systems with logging, metrics, and tracing capabilities, deploy to production, and monitor SLAs and associated costs.
Training Delivery Model
- Interactive instructional sessions and facilitated discussions.
- Extensive exercises and practical application tasks.
- Real-time implementation within a live laboratory environment.
Customization Options
- Interested parties may contact the provider to coordinate a tailored training program aligned with specific organizational needs.
Building Coding Agents with Devstral: From Agent Design to Tooling
14 HoursDevstral is an open-source framework engineered for the development and deployment of coding agents. These agents interact with codebases, developer tools, and application programming interfaces to improve engineering efficiency and operational standards for government systems.
This instructor-led training, available online or on-site, targets intermediate to advanced machine learning engineers, developer tooling specialists, and site reliability engineers. The objective is to enable participants to design, implement, and optimize coding agents using Devstral within a formal operational context.
Upon completion of this training, participants will be capable of:
- Installing and configuring Devstral for the development of coding agents.
- Designing agentic workflows for codebase analysis and modification.
- Integrating coding agents with developer tools and external APIs.
- Applying best practices for the secure and efficient deployment of agents.
Instructional Methodology
- Interactive lectures and facilitated discussions.
- Extensive practical exercises and skill-building activities.
- Hands-on implementation within a live laboratory environment.
Customization Options for Government
- Contact our team to arrange a customized training session tailored to specific government requirements.
Open-Source Model Ops: Self-Hosting, Fine-Tuning and Governance with Devstral & Mistral Models
14 HoursDevstral and Mistral models represent open-source artificial intelligence technologies engineered for flexible deployment, precise fine-tuning, and scalable integration within organizational infrastructure.
This instructor-led training, available in online or onsite formats, targets intermediate to advanced machine learning engineers, platform teams, and research professionals. The curriculum focuses on self-hosting, fine-tuning, and governing Mistral and Devstral models for production environments, with specific relevance to secure and accountable operations for government.
Upon completion, participants will be equipped to:
- Configure and manage self-hosted environments for Mistral and Devstral models.
- Execute fine-tuning processes to enhance domain-specific performance.
- Deploy versioning, monitoring, and lifecycle governance frameworks.
- Maintain security, compliance, and responsible usage protocols for open-source models for government.
Course Format
- Interactive lectures facilitated by expert discussion.
- Practical exercises focused on self-hosting and fine-tuning techniques.
- Live-lab implementation of governance and monitoring pipelines.
Customization Availability
- Prospective learners may contact our office to arrange customized training sessions for this course.
LangGraph Applications in Finance
35 HoursLangGraph serves as a framework for constructing stateful, multi-agent large language model (LLM) applications through composable graphs, featuring persistent state management and precise execution control.
This instructor-led, live training session (available online or on-site) is tailored for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance for government and regulated sectors.
Upon completion of this training, participants will be proficient in the following areas:
- Designing financial workflows within LangGraph that adhere to regulatory and audit mandates.
- Integrating financial data standards and ontologies into graph state management and operational tooling.
- Implementing reliability, safety, and human-in-the-loop controls for critical financial processes.
- Deploying, monitoring, and optimizing LangGraph systems to meet performance targets, cost efficiency, and service level agreements (SLAs).
Course Format
- Interactive lectures and structured discussions.
- Extensive practical exercises and skill-building activities.
- Hands-on implementation within a live laboratory environment.
Course Customization Options
- To request a customized training curriculum for this course, please contact the provider to coordinate arrangements.
LangGraph Foundations: Graph-Based LLM Prompting and Chaining
14 HoursLangGraph serves as a specialized framework for constructing graph-based LLM applications, enabling advanced features such as strategic planning, conditional branching, tool utilization, persistent memory, and controlled execution environments.
This instructor-led, live training program, available online or onsite, is designed for junior-level developers, prompt engineers, and data professionals seeking to engineer robust, multi-step LLM workflows utilizing LangGraph.
Upon completion of this program, participants will possess the capability to:
- Articulate fundamental LangGraph components (nodes, edges, state) and their applicable contexts.
- Construct prompt chains that support branching, tool invocation, and memory retention.
- Integrate retrieval mechanisms and external APIs into graph-based workflows for government use cases.
- Test, debug, and assess LangGraph applications to ensure reliability and safety standards.
Instructional Methodology
- Interactive lectures combined with facilitated group discussions.
- Guided laboratory sessions and code analysis within a secure sandbox environment.
- Scenario-driven exercises focused on architectural design, testing, and evaluation.
Customization Capabilities
- To arrange a customized training program for government agencies, please contact our team for specific requirements.
LangGraph in Healthcare: Workflow Orchestration for Regulated Environments
35 HoursLangGraph facilitates stateful, multi-actor workflows leveraging Large Language Models (LLMs) with precise control over execution paths and state persistence. Within the public health sector, these capabilities are essential for ensuring regulatory compliance, achieving interoperability, and developing decision-support systems aligned with government medical operations.
This instructor-led, live training (available online or onsite) is designed for intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based healthcare solutions for government, while addressing regulatory, ethical, and operational complexities.
Upon completion of this training, participants will be able to:
- Design healthcare-specific LangGraph workflows with a focus on regulatory compliance and auditability.
- Integrate LangGraph applications with medical ontologies and standards (FHIR, SNOMED CT, ICD) required for government data exchange.
- Apply best practices for reliability, traceability, and explainability in sensitive public sector environments.
- Deploy, monitor, and validate LangGraph applications in healthcare production settings for government use.
Format of the Course
- Interactive lectures and facilitated discussions.
- Hands-on exercises utilizing real-world public sector case studies.
- Implementation practice in a live laboratory environment.
Course Customization Options
- To request a customized training program tailored to specific government agency needs, please contact us to arrange details.
LangGraph for Legal Applications
35 HoursBuilding Dynamic Workflows with LangGraph and LLM Agents
14 HoursLangGraph 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. This infrastructure is well-suited for the automation and customization of content pipelines for government operations.
This instructor-led, live training session, available in online or onsite formats, targets intermediate-level professionals, including content strategists and automation developers. The objective is to implement dynamic, branching email campaigns and automated content generation systems using LangGraph.
Upon completion of this training, participants will possess the ability to:
- Design graph-structured content and email workflows incorporating conditional logic.
- Integrate LLMs, application programming interfaces (APIs), and external data sources to drive automated personalization.
- Manage state, memory, and contextual data across multi-step campaign executions.
- Evaluate, monitor, and optimize workflow performance and final delivery outcomes.
Course Structure and Delivery Method
- Interactive instructional sessions and facilitated group discussions.
- Practical laboratory exercises focused on implementing email workflows and content pipelines.
- Scenario-based assignments emphasizing personalization, audience segmentation, and branching logic.
Course Customization and Tailored Solutions
- For inquiries regarding customized training solutions tailored to specific operational needs for government, please contact the appropriate administrative office.
Le Chat Enterprise: Private ChatOps, Integrations & Admin Controls
14 HoursLe Chat Enterprise serves as a private ChatOps solution that delivers secure, customizable, and governed conversational AI capabilities for organizations, specifically designed for government operations, with robust support for RBAC, SSO, connectors, and enterprise application integrations.
This instructor-led, live training program (available online or onsite) is designed for intermediate-level product managers, IT leads, solution engineers, and security/compliance teams seeking to deploy, configure, and govern Le Chat Enterprise within enterprise and government environments.
Upon completion of this training, participants will be equipped to:
- Establish and configure Le Chat Enterprise for secure government deployments.
- Activate RBAC, SSO, and compliance-driven control mechanisms.
- Integrate Le Chat with enterprise applications and secure data stores for government use.
- Develop and implement governance and administrative playbooks for ChatOps operations.
Course Delivery Format
- Interactive lectures and structured discussions.
- Extensive exercises and practical application tasks.
- Hands-on implementation within a live laboratory environment.
Course Customization Options for Government
- To request a tailored training program for this course, please contact us to arrange specific requirements.
Cost-Effective LLM Architectures: Mistral at Scale (Performance / Cost Engineering)
14 HoursProductizing Conversational Assistants with Mistral Connectors & Integrations
14 HoursMistral AI serves as an open platform that empowers organizations to develop and embed conversational assistants within both internal operations and external service delivery channels for government and enterprise environments.
This instructor-led, live training session—available in online or on-site formats—is designed for product managers, full-stack developers, and integration engineers at beginner to intermediate levels. The curriculum focuses on the strategic design, integration, and operationalization of conversational assistants utilizing Mistral’s connector and integration frameworks.
Upon completion of this training, participants will possess the capability to:
- Integrate Mistral conversational models with enterprise-grade and SaaS infrastructure components.
- Implement retrieval-augmented generation (RAG) to ensure grounded, fact-based responses.
- Architect user experience patterns for both internal operational tools and external service points.
- Deploy assistants into functional workflows to address specific operational requirements.
Training Delivery Format
- Interactive instructional sessions and facilitated discussions.
- Practical exercises focused on system integration.
- Live laboratory sessions for the development of conversational prototypes.
Customization Availability
- Organizations may request tailored training modules for government or specific operational needs by contacting the provider for scheduling.
Enterprise-Grade Deployments with Mistral Medium 3
14 HoursMistral Medium 3 is a high-performance, multimodal large language model engineered for production-grade implementation within enterprise and government sectors.
This instructor-led, live training session, available online or on-site, is designed for intermediate to advanced AI/ML engineers, platform architects, and MLOps teams seeking to deploy, optimize, and secure Mistral Medium 3 for critical enterprise and public sector applications.
Upon completion of this training, participants will be equipped to:
- Deploy Mistral Medium 3 through API integrations and self-hosted infrastructure options.
- Enhance inference performance while managing operational costs effectively.
- Execute multimodal use cases leveraging Mistral Medium 3 capabilities.
- Enforce security and compliance standards aligned with enterprise and governmental requirements.
Course Delivery Format
- Interactive instructional sessions and facilitated discussions.
- Extensive practical exercises and proficiency drills.
- Hands-on implementation within a controlled live-lab environment.
Customization Options for Government Needs
- To request a customized training curriculum tailored for government requirements, please contact the program office to coordinate scheduling and scope.
Mistral for Responsible AI: Privacy, Data Residency & Enterprise Controls
14 HoursMistral AI operates as an open, enterprise-oriented platform designed to facilitate the secure, compliant, and responsible deployment of artificial intelligence solutions.
This instructor-led, live instructional session, available in either virtual or on-site formats, is tailored for mid-level compliance officers, security engineers, and legal/operational stakeholders. The objective is to implement responsible AI practices using Mistral by applying privacy safeguards, data residency controls, and enterprise-level governance mechanisms relevant for government and public sector operations.
Upon completion of this training, participants will demonstrate the ability to:
- Deploy privacy-preserving methodologies within Mistral environments.
- Execute data residency strategies to satisfy statutory and regulatory obligations.
- Configure enterprise-grade security controls, including RBAC, SSO, and audit logging.
- Assess vendor capabilities and deployment models for regulatory alignment.
Instructional Methodology
- Facilitated instruction through lectures and collaborative discussion.
- Analysis of compliance-centric scenarios and practical exercises.
- Practical application of enterprise AI control frameworks.
Program Customization
- Interested parties may contact the organization to discuss tailored training options for this course.
Multimodal Applications with Mistral Models (Vision, OCR, & Document Understanding)
14 HoursMistral models constitute open-source artificial intelligence technologies that have expanded into multimodal workflows, facilitating both linguistic and visual tasks for enterprise and research contexts.
This live, instructor-led training (available online or onsite) is designed for intermediate-level machine learning researchers, applied engineers, and product teams intending to develop multimodal applications using Mistral models, particularly those involving OCR and document comprehension pipelines.
Upon completion of this training, participants will possess the ability to:
- Install and configure Mistral models for multimodal operations.
- Implement OCR workflows and integrate them with NLP processing pipelines.
- Architect document comprehension applications for enterprise operational needs.
- Develop vision-text search functionalities and assistive user interface components.
Course Structure
- Interactive instruction and facilitated discussion.
- Practical coding exercises.
- Live laboratory implementation of multimodal pipelines.
Customization Options for the Course
- To request a customized training program for this course, please contact us to schedule.
