Large Language Models (LLMs) Training in Tulsa

This instructor-led, live training in Tulsa (online or onsite) is designed for senior management professionals who wish to understand the capabilities of large language models (LLMs), explore their potential impact on business operations, and evaluate practical uses of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks like content creation, data summarization, and decision support.

By the end of this training, participants will be able to:

• Understand what LLMs are and how tools like ChatGPT and Copilot operate.
• Utilize prompt techniques to achieve practical, reliable results from LLMs.
• Assess real use cases such as email drafting, document summarization, and productivity automation.
• Identify investment opportunities and strategic applications for AI adoption in the public sector for government operations.

This instructor-led, live training in [location] (online or onsite) is aimed at senior management teams who wish to understand the strategic value of Large Language Models (LLMs) and enterprise AI tools. Participants will explore how to integrate these tools into high-level workflows for government, draft better prompts, and evaluate opportunities for increased productivity and return on investment (ROI) through AI adoption. By the end of this training, participants will be able to: - Understand how LLMs function and how tools like ChatGPT and Copilot apply them. - Use prompt-based interactions to automate and accelerate tasks. - Apply AI tools to real scenarios such as email drafting, report summarization, and agreement review for government. - Evaluate strategic benefits, limitations, and licensing considerations for LLM adoption.

This instructor-led, live training in Tulsa (online or onsite) is designed for intermediate to advanced AI researchers, data scientists, and developers who seek to understand, fine-tune, and implement Meta AI's Large Language Models for various NLP applications.

By the end of this training, participants will be able to:

• Comprehend the architecture and functionality of Meta AI's Large Language Models.
• Configure and fine-tune Meta AI LLMs for specific use cases.
• Develop LLM-based applications, including text summarization, chatbots, and sentiment analysis.
• Optimize and deploy large language models efficiently to support various public sector workflows for government.

This instructor-led, live training (available online or on-site) is designed for intermediate-level AI professionals, business analysts, and technology leaders who seek to understand the principles of generative AI and the applications of large language models (LLMs) in business settings. Participants will gain insights into transformers, prompt engineering, and ethical considerations when deploying these models for real-world solutions.

By the end of this training, participants will be able to:

• Comprehend the foundational principles of generative AI and large language models.
• Implement and fine-tune LLMs for specific business applications.
• Utilize prompt engineering techniques to optimize model outputs.
• Identify ethical considerations and manage risks associated with LLM deployment, ensuring alignment with public sector workflows, governance, and accountability for government use cases.

This instructor-led, live training (online or onsite) is designed for intermediate-level AI professionals, ethicists, data scientists and engineers, as well as policy makers and stakeholders who wish to understand and navigate the ethical landscape of large language models (LLMs). By the end of this training, participants will be able to: - Identify ethical issues and challenges associated with LLMs. - Apply ethical frameworks and principles to the deployment of LLMs. - Evaluate the societal impact of LLMs and mitigate potential risks. - Develop strategies for responsible AI development and usage, ensuring alignment with public sector workflows and accountability standards for government.

This instructor-led, live training (online or onsite) is designed for intermediate-level natural language processing practitioners, data scientists, content creators, translators, and government entities who wish to utilize large language models (LLMs) for language translation and creating multilingual content. By the end of this training, participants will be able to: - Understand the principles of cross-lingual learning and translation with LLMs. - Implement LLMs for translating content between various languages. - Create and manage multilingual datasets for training LLMs. - Develop strategies for maintaining consistency and quality in translation, ensuring alignment with public sector workflows and governance standards.

This instructor-led, live training (conducted either online or onsite) is designed for intermediate-level financial analysts, data scientists, and investment professionals who aim to leverage large language models (LLMs) for financial market analysis and prediction. By the end of this training, participants will be able to: - Understand the application of LLMs in financial market analysis. - Utilize LLMs to process financial news, reports, and data to gain market insights. - Develop predictive models for stock prices, market trends, and economic indicators. - Integrate LLM-generated insights into investment decision-making processes, enhancing the accuracy and efficiency of financial strategies for government and private sector applications.

This instructor-led, live training (offered online or onsite) is designed for intermediate-level environmental scientists and researchers, data analysts, and policymakers and environmental advocates who wish to leverage large language models (LLMs) for environmental modeling and analysis. By the end of this training, participants will be able to: - Understand the application of LLMs in environmental science. - Utilize LLMs to analyze and model environmental data. - Interpret LLM outputs for environmental impact assessments. - Communicate findings effectively to inform policy and conservation efforts for government and public sector initiatives.

This instructor-led, live training, available both online and onsite, is designed for intermediate-level VR and AR developers, game designers, and AI engineers who are interested in integrating Large Language Models (LLMs) into their VR and AR applications to enhance user engagement and responsiveness. By the end of this training, participants will be able to: - Comprehend the role of LLMs in developing immersive VR and AR experiences. - Create VR and AR applications that leverage LLMs for interactive dialogues and dynamic content generation. - Integrate LLMs with VR and AR development tools to improve user interaction and engagement. - Implement best practices for designing AI-driven narratives and interactions in virtual environments, ensuring alignment with public sector workflows and governance standards for government.

This instructor-led, live training in Tulsa (online or onsite) is aimed at intermediate-level data scientists, machine learning engineers, and software developers who wish to apply Large Language Models (LLMs) to multimodal data for advanced AI applications for government. By the end of this training, participants will be able to: - Understand the principles of multimodal learning with LLMs. - Implement LLMs to process and analyze text, image, and audio data. - Develop applications that leverage the strengths of multimodal data integration. - Evaluate the performance of multimodal LLM systems.

This instructor-led, live training (available online or onsite) is designed for intermediate-level cybersecurity professionals and data scientists who wish to leverage Large Language Models (LLMs) to enhance cybersecurity measures and threat intelligence for government. By the end of this training, participants will be able to: - Understand the role of LLMs in enhancing cybersecurity. - Implement LLMs for threat detection and analysis. - Utilize LLMs for security automation and response. - Integrate LLMs with existing security infrastructure for government.

This instructor-led, live training (offered online or onsite) is designed for intermediate-level data scientists and business analysts who wish to leverage large language models (LLMs) to predict trends and behaviors across various sectors. By the end of this training, participants will be able to: - Understand the foundational principles of LLMs and their application in predictive analytics. - Implement LLMs to analyze and forecast data in diverse industries. - Assess the effectiveness of predictive models utilizing LLMs. - Integrate LLMs with existing data processing workflows for government and other organizations.

This instructor-led, live training (online or onsite) is designed for intermediate-level data scientists who aim to achieve a thorough understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL). By the end of this training, participants will be able to: - Comprehend the components and functionality of transformer models. - Optimize and fine-tune LLMs for specific tasks and applications. - Grasp the core principles and methodologies of reinforcement learning. - Understand how reinforcement learning techniques can improve the performance of LLMs for government use.

This instructor-led, live training in [location] (online or onsite) is designed for intermediate-level content creators, marketers, and educational technologists who aim to leverage the power of Large Language Models (LLMs) for generating high-quality, diverse, and engaging content across various domains. By the end of this training, participants will be able to: - Understand the capabilities of LLMs and their application in content generation. - Set up and use LLMs for producing a variety of content types. - Apply best practices for prompting and fine-tuning LLMs to achieve desired outputs. - Evaluate the quality of AI-generated content and refine it for specific audiences. - Explore advanced techniques for creative and multi-modal content generation with LLMs, ensuring alignment with public sector workflows and governance standards for government.

This instructor-led, live training (available online or onsite) is aimed at educators, EdTech professionals, and researchers with varying levels of experience who wish to leverage large language models (LLMs) for creating personalized educational experiences. By the end of this training, participants will be able to: - Understand the architecture and capabilities of LLMs. - Identify opportunities for personalization in educational content using LLMs. - Design adaptive learning platforms that utilize LLMs for content personalization. - Implement LLM-driven strategies for enhancing student engagement and learning outcomes. - Evaluate the effectiveness of LLMs in educational settings and make data-driven decisions for government and institutional improvement.

This instructor-led, live training (online or onsite) is designed for intermediate-level machine learning practitioners and artificial intelligence developers who aim to refine and deploy open-weight models such as LLaMA, Mistral, and Qwen for specific business or internal applications. By the end of this training, participants will be able to: - Understand the ecosystem and differences among open-source large language models. - Prepare datasets and fine-tuning configurations suitable for models like LLaMA, Mistral, and Qwen. - Execute fine-tuning pipelines using Hugging Face Transformers and PEFT. - Evaluate, save, and deploy fine-tuned models in secure environments, ensuring compliance with standards for government use.

This instructor-led, live training (available online or onsite) is designed for beginner to intermediate software developers and data scientists who are interested in implementing large language models (LLMs) in speech recognition and synthesis systems for government applications. By the end of this training, participants will be able to: - Understand the role of LLMs in speech technologies. - Implement LLMs to enhance the accuracy of speech recognition and produce natural-sounding speech synthesis. - Integrate LLMs with existing speech recognition engines and speech synthesizers. - Evaluate and improve the performance of speech systems using LLMs. - Stay informed about current trends and future directions in speech technologies for government use.

This instructor-led, live training in Tulsa (online or onsite) is designed for government customer support and IT professionals at the beginner to intermediate level who wish to implement Large Language Models (LLMs) to create responsive and intelligent customer support chatbots. By the end of this training, participants will be able to: - Understand the fundamentals and architecture of LLMs. - Design and integrate LLMs into government customer support systems. - Enhance the responsiveness and user experience of chatbots for government use. - Address ethical considerations and ensure compliance with industry standards. - Deploy and maintain an LLM-based chatbot for real-world applications in a government context.

This instructor-led, live training (online or onsite) is designed for intermediate-level data scientists and AI engineers who aim to refine large language models more cost-effectively and efficiently using techniques such as LoRA, Adapter Tuning, and Prefix Tuning. By the end of this training, participants will be able to: - Understand the theoretical foundations of parameter-efficient fine-tuning methods. - Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT for government applications. - Evaluate the performance and cost trade-offs of PEFT methods compared to full fine-tuning. - Deploy and scale fine-tuned LLMs with minimized compute and storage requirements.

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced machine learning engineers, AI developers, and data scientists who wish to learn how to use QLoRA to efficiently fine-tune large models for specific tasks and customizations. By the end of this training, participants will be able to: - Understand the theory behind QLoRA and quantization techniques for large language models. - Implement QLoRA in fine-tuning large language models for domain-specific applications. - Optimize fine-tuning performance on limited computational resources using quantization methods. - Deploy and evaluate fine-tuned models efficiently in real-world scenarios, ensuring alignment with public sector workflows and governance standards for government.

This instructor-led, live training (online or onsite) is designed for intermediate-level data and marketing professionals who aim to apply large language models (LLMs) to analyze and interpret public sentiment from various text sources such as social media posts, product reviews, and customer feedback. By the end of this training, participants will be able to: - Understand the principles of sentiment analysis and its application using LLMs. - Preprocess and prepare datasets for sentiment analysis. - Train and fine-tune LLMs to accurately reflect sentiment in text. - Analyze sentiment in real-time from social media and other text sources. - Integrate sentiment analysis findings into business strategies and decision-making processes, ensuring alignment with public sector workflows, governance, and accountability for government.

This instructor-led, live training (online or onsite) is designed for intermediate-level software developers and technical writers who wish to leverage Large Language Models (LLMs) to enhance their coding workflow and produce detailed, comprehensive documentation. By the end of this training, participants will be able to: - Understand the role of LLMs in automating code generation and software documentation. - Utilize LLMs to create accurate and efficient code snippets and documentation. - Integrate LLMs into their software development lifecycle for improved productivity. - Maintain high-quality documentation standards using automated tools. - Address ethical considerations and best practices for using AI in software development, ensuring alignment with public sector workflows and governance for government.

This instructor-led, live training (available online or onsite) is designed for intermediate-level business professionals and data analysts who wish to leverage the power of Large Language Models (LLMs) for extracting valuable business insights. By the end of this training, participants will be able to: - Understand the foundational concepts and applications of LLMs in the context of business intelligence. - Apply LLMs to analyze extensive datasets and derive actionable insights. - Integrate LLM-driven analytics into strategic decision-making processes for government and private sector operations. - Evaluate the ethical considerations and best practices associated with using LLMs in a business environment. - Anticipate future trends in artificial intelligence and prepare for the evolving landscape of business intelligence.

This instructor-led, live training (online or onsite) is designed for intermediate to advanced developers and data scientists who wish to master LlamaIndex for developing innovative language model-powered applications for government. By the end of this training, participants will be able to: - Set up and configure LlamaIndex for use with language models. - Index and query custom datasets using LlamaIndex to enhance language model functionality. - Design and develop sophisticated applications that utilize LlamaIndex and language models. - Understand and apply best practices for working with language models and LlamaIndex. - Navigate the ethical considerations involved in deploying language model-powered applications.

This instructor-led, live training (online or onsite) is designed for intermediate-level AI researchers, machine learning professionals, and data scientists who aim to leverage LlamaIndex to enhance the capabilities of AI models, making them more accurate and reliable for various applications. By the end of this training, participants will be able to: - Understand the principles and components of LlamaIndex. - Ingest and structure data for use with large language models (LLMs). - Implement context augmentation to improve AI model performance. - Integrate LlamaIndex into existing AI systems and workflows for government.

This instructor-led, live training (conducted online or onsite) is designed for intermediate-level professionals who aim to harness the capabilities of prompt engineering and few-shot learning to enhance the performance of Large Language Models (LLMs) for real-world applications. By the end of this training, participants will be able to: - Understand the foundational principles of prompt engineering and few-shot learning. - Develop effective prompts for a variety of natural language processing tasks. - Utilize few-shot techniques to adapt LLMs with minimal data requirements. - Optimize LLM performance to meet practical needs, ensuring alignment with public sector workflows and governance standards for government.

LangGraph is a framework designed for building stateful, multi-actor language model applications as composable graphs with persistent state and precise control over execution. This instructor-led, live training (available online or onsite) is aimed at intermediate to advanced-level professionals who wish to design, implement, and operate LangGraph-based solutions for government 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 ensure 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. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

This instructor-led, live training (online or onsite) is designed for advanced-level engineers, AI specialists, and localization leads who aim to implement large language model (LLM) systems for automated translation, quality evaluation, and enterprise governance. By the end of this training, participants will be able to: - Construct enterprise-grade LLM localization pipelines that integrate both open and proprietary models. - Implement automated quality assurance workflows and metrics to ensure consistent translations. - Establish governance and approval frameworks for the production of multilingual content. - Deploy scalable, auditable LLM-based localization systems in secure environments, ensuring compliance with standards for government.

AI for SQL is the application of artificial intelligence and large language models (LLMs) to automate, optimize, and enhance the way SQL queries are generated, executed, and interpreted within enterprise data environments. This instructor-led, live training (online or onsite) is aimed at intermediate-level data engineers and technical leads who wish to integrate AI capabilities into SQL workflows to enable natural language querying, intelligent optimization, and automated data analysis for government and other public sector entities. By the end of this training, participants will be able to: - Integrate LLMs such as GPT, DeepSeek, LLaMA, Qwen, and Mistral into SQL environments. - Build natural-language-to-SQL pipelines for conversational data access. - Implement AI-driven query optimization and error detection. - Design secure, auditable AI-SQL workflows for enterprise use. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for government or other specific needs, please contact us to arrange.

LangGraph is a framework designed for building stateful, multi-actor language model applications as composable graphs with persistent state and control over execution. This instructor-led, live training (online or onsite) is aimed at intermediate to advanced-level professionals who wish to design, implement, and operate LangGraph-based solutions in the finance sector, ensuring proper governance, observability, and compliance for government and private entities. By the end of this training, participants will be able to: - Design finance-specific LangGraph workflows aligned with regulatory and audit requirements. - Integrate financial data standards and ontologies into graph state and tooling. - Implement reliability, safety, and human-in-the-loop controls for critical processes. - Deploy, monitor, and optimize LangGraph systems for performance, cost, and service level agreements (SLAs). **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for government or private sector needs, please contact us to arrange.

Vertex AI provides robust tools for developing multimodal large language model (LLM) workflows that seamlessly integrate text, audio, and image data into a single pipeline. With support for long context windows and Gemini API parameters, it facilitates advanced applications in planning, reasoning, and cross-modal intelligence. This instructor-led, live training (online or onsite) is designed for intermediate to advanced-level practitioners who aim to design, build, and optimize multimodal AI workflows using Vertex AI. By the end of this training, participants will be able to: - Utilize Gemini models for handling multimodal inputs and outputs. - Implement long-context workflows for complex reasoning tasks. - Design pipelines that incorporate text, audio, and image analysis. - Optimize Gemini API parameters to enhance performance and cost efficiency. **Format of the Course** - Interactive lecture and discussion - Hands-on labs with multimodal workflows - Project-based exercises for applied multimodal use cases **Course Customization Options** - To request a customized training for government or other specific needs, please contact us to arrange.

The Devstral and Mistral models are open-source artificial intelligence technologies designed for flexible deployment, fine-tuning, and scalable integration. This instructor-led, live training (available online or onsite) is targeted at intermediate to advanced machine learning engineers, platform teams, and research engineers who aim to self-host, fine-tune, and govern the use of Mistral and Devstral models in production environments for government. 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 optimize performance for specific domains. - Implement versioning, monitoring, and lifecycle governance practices. - Ensure security, compliance, and responsible usage of open-source models. **Format of the Course** - Interactive lectures and discussions. - 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 government use, please contact us to arrange.

LangGraph enables stateful, multi-actor workflows powered by LLMs with precise control over execution paths and state persistence. In healthcare, these capabilities are essential for compliance, interoperability, and building decision-support systems that align with medical workflows. This instructor-led, live training (online or onsite) is aimed at intermediate to advanced professionals who wish to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges for government and private sector applications. By the end 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.

This instructor-led, live training (online or onsite) is designed for intermediate-level AI developers and localization engineers who are interested in creating scalable, automated translation pipelines using both proprietary and open-source large language models (LLMs). By the end of this training, participants will be able to: - Design and deploy translation workflows utilizing modern LLM frameworks and APIs. - Integrate open-source and commercial models into robust translation systems. - Enhance translation quality through fine-tuning, prompt engineering, and automation. - Implement cost-effective and compliant translation infrastructure for enterprise environments, ensuring alignment with public sector workflows and governance for government.

LangGraph is a framework designed for building stateful, multi-actor language model 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 professionals for government, 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 through 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. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in [location] (online or onsite) is designed for intermediate-level developers who wish to learn how to utilize generative artificial intelligence with large language models for various tasks and domains. By the end of this training, participants will be able to: - Define what generative AI is and explain its mechanisms. - Describe the transformer architecture that underpins large language models. - Utilize empirical scaling laws to optimize large language models for different tasks and constraints. - Apply state-of-the-art tools and methods to train, fine-tune, and deploy large language models. - Discuss the opportunities and risks of generative AI for government and business. This training aligns with public sector workflows, governance, and accountability, ensuring that participants are well-equipped to leverage these technologies effectively and responsibly.

Large Language Models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming how DevOps teams automate tasks like change tracking, test generation, and alert triage by simulating human-like collaboration and decision-making processes.

This instructor-led, live training (available online or onsite) is designed for advanced-level engineers who aim to design and implement DevOps automation workflows powered by LLMs and multi-agent systems for government applications.

By the end of this training, participants will be able to:

• Integrate LLM-based agents into CI/CD workflows to enhance smart automation capabilities.
• Automate test generation, commit analysis, and change summaries using these advanced agents.
• Coordinate multiple agents for effective alert triaging, response generation, and DevOps recommendations.
• Build secure and maintainable agent-powered workflows utilizing open-source frameworks.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical activities.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for government, please contact us to arrange.

Mistral 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, specifically tailored for government applications.

By the end of this training, participants will be able to:

• Implement scalable deployment patterns for Mistral Medium 3 in a government context.
• Apply batching, quantization, and efficient serving strategies to meet public sector requirements.
• Optimize inference costs while maintaining performance for government workloads.
• Design production-ready serving topologies for enterprise and government workloads.

Format of the Course

• Interactive lecture and discussion tailored to public sector needs.
• Lots of exercises and practice relevant to government operations.
• Hands-on implementation in a live-lab environment designed for government use cases.

Course Customization Options

• To request a customized training for this course, specifically adapted for government agencies, please contact us to arrange.

Postgres is an advanced open-source relational database that can serve as a foundation for AI-powered systems and data intelligence applications. This instructor-led, live training (online or onsite) is aimed at intermediate-level database professionals and developers who wish to integrate, manage, and optimize AI capabilities directly within Postgres for government use. By the end of this training, participants will be able to: - Set up and configure Postgres extensions for AI workloads. - Implement embeddings and similarity search using pgvector. - Integrate open source and proprietary LLMs with Postgres for real-time insights. - Optimize Postgres for handling AI-driven queries and workflows. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in [location] (online or onsite) is designed for intermediate to advanced AI developers, architects, and product managers who seek to identify and mitigate risks associated with LLM-powered applications. These risks include prompt injection, data leakage, and unfiltered output. The training will cover the implementation of security controls such as input validation, human-in-the-loop oversight, and output guardrails. By the end of this training, participants will be able to: - Understand the core vulnerabilities of LLM-based systems. - Apply secure design principles to LLM application architecture. - Utilize tools like Guardrails AI and LangChain for validation, filtering, and safety measures. - Integrate techniques such as sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines. This training is tailored to enhance the security and reliability of AI applications for government use, ensuring they meet the highest standards of governance and accountability.

LangGraph is a graph-based orchestration framework designed to enable conditional, multi-step workflows involving language models and tools, making it ideal for automating and personalizing content pipelines. This instructor-led, live training (available online or onsite) is tailored for intermediate-level marketers, content strategists, and automation developers who aim 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 incorporating conditional logic. - Integrate language models, 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 focusing on implementing email workflows and content pipelines. - Scenario-based exercises covering personalization, segmentation, and branching logic. **Course Customization Options for Government** To request a customized training for government agencies, please contact us to arrange.

Le Chat Enterprise is a private ChatOps solution designed to provide secure, customizable, and governed conversational AI capabilities for organizations. It supports role-based access control (RBAC), single sign-on (SSO), connectors, and integrations with enterprise applications. This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, IT leads, solution engineers, and security/compliance teams who wish to deploy, configure, and govern Le Chat Enterprise in enterprise environments for government use. By the end of this training, participants will be able to: - Set up and configure Le Chat Enterprise for secure deployments. - Enable RBAC, SSO, and compliance-driven controls. - Integrate Le Chat with enterprise applications and data stores. - Design and implement governance and administrative playbooks for ChatOps. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

Devstral 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 to advanced-level ML engineers, developer-tooling teams, and SREs who wish to design, implement, and optimize coding agents using Devstral for government applications. 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 in alignment with public sector standards. **Format of the Course** - Interactive lecture and discussion. - Extensive exercises and practice sessions. - Hands-on implementation in a live-lab environment. **Course Customization Options** - To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Tulsa (online or onsite) is designed for intermediate to advanced professionals who seek to customize pre-trained models for specific tasks and datasets. By the end of this training, participants will be able to: - Comprehend the principles of fine-tuning and their applications. - Prepare datasets for the fine-tuning of pre-trained models. - Fine-tune large language models (LLMs) for natural language processing (NLP) tasks. - Enhance model performance and address common challenges. This training is tailored to meet the needs of professionals working in various sectors, including those for government, ensuring that participants are well-equipped to apply these skills in their respective fields.

LangGraph is a framework designed for composing graph-structured workflows that support branching, tool use, memory, and controllable execution. This instructor-led, live training (available online or on-site) is targeted at intermediate-level engineers and product teams who wish to integrate LangGraph’s graph logic with LLM agent loops to develop dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems for government. 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 to ensure robust execution. - Integrate retrieval mechanisms, APIs, and structured outputs into agent loops. - Evaluate, monitor, and enhance 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.

The LLMs for Code Understanding, Refactoring, and Documentation is a technical course designed to leverage large language models (LLMs) to enhance code quality, reduce technical debt, and automate documentation tasks across software teams in the public sector.

This instructor-led, live training (available online or onsite) is targeted at intermediate to advanced-level software professionals who seek to utilize LLMs such as GPT to analyze, refactor, and document complex or legacy codebases more effectively for government applications.

By the end of this training, participants will be able to:

• Use LLMs to explain code, dependencies, and logic in unfamiliar repositories.
• Identify and refactor anti-patterns to improve code readability.
• Automatically generate and maintain inline comments, README files, and API documentation.
• Integrate LLM-driven insights into existing continuous integration/continuous deployment (CI/CD) and review workflows for government projects.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course tailored to specific government needs, please contact us to arrange.

This instructor-led, live training in [location] (online or onsite) is designed for intermediate-level data scientists, AI developers, and AI enthusiasts who aim to utilize large language models (LLMs) to perform various natural language processing tasks and create innovative and diverse content for different applications. By the end of this training, participants will be able to: - Set up a development environment with LLMs and essential tools. - Proficiently execute natural language understanding (NLU) and natural language inference (NLI) tasks using LLMs. - Effectively extract, infer, and utilize knowledge graphs. - Generate and manage dialogues with LLMs for conversational applications. - Assess the quality and diversity of content generated by LLMs and generative AI. - Apply ethical principles to ensure fairness and responsible use of LLMs, aligning with standards for government.

LangGraph is a framework designed for building graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution. This instructor-led, live training (available 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 for government. 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 applications 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.

This instructor-led, live training (online or onsite) is designed for government developers at beginner to intermediate levels who wish to utilize Large Language Models for various natural language tasks. By the end of this training, participants will be able to: - Set up a development environment that includes a popular LLM. - Create and fine-tune a basic LLM on a custom dataset. - Apply LLMs to different natural language tasks such as text summarization, question answering, text generation, and more. - Debug and evaluate LLMs using tools like TensorBoard, PyTorch Lightning, and Hugging Face Datasets. This training is tailored to enhance the capabilities of government developers in leveraging advanced technologies for government applications.

Mistral Medium 3 is a high-performance, multimodal large language model designed for production-grade deployment across enterprise and government environments.

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced AI/ML engineers, platform architects, and MLOps teams who wish to deploy, optimize, and secure Mistral Medium 3 for government 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 and government environments.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Upon completion of this course, participants will be able to: - Gain a comprehensive understanding of the architecture and functionality of modern Large Language Models (LLMs). - Create structured and robust technical prompts for styling, testing, refactoring, and automated quality assurance. - Develop AI-aware wrappers and microservices that integrate seamlessly within enterprise development ecosystems for government. - Implement comprehensive Retrieval-Augmented Generation (RAG) pipelines for organizational knowledge retrieval. - Manage the security, privacy, and audit aspects of AI-driven code and data interactions.