NLP: Natural Language Processing with R Training Course

LangGraph is a framework designed for creating stateful, multi-actor LLM applications as composable graphs, featuring persistent state and execution control.

This instructor-led live training, available online or onsite, targets advanced AI platform engineers, AI DevOps specialists, and ML architects looking to optimize, debug, monitor, and operate production-grade LangGraph systems.

Upon completing this training, participants will be able to:

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Build reliability into systems using 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 application.
• Hands-on implementation in a live-lab environment.

Customization Options

• For customized training requests, please contact us to arrange your session.

Devstral is an open-source framework engineered for the creation and operation of coding agents capable of interacting with code repositories, developer utilities, and APIs to boost engineering productivity.

This instructor-led, live training session (available online or onsite) targets intermediate to advanced ML engineers, developer-tooling teams, and Site Reliability Engineers (SREs) seeking to design, implement, and optimize coding agents using Devstral.

Upon completion of this training, participants will be equipped to:

• Establish and configure the Devstral environment for coding agent development.
• Architect agentic workflows tailored for codebase exploration and modification.
• Integrate coding agents seamlessly with developer tools and APIs.
• Adopt best practices for secure and efficient agent deployment.

Course Format

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

Customization Options

• To request tailored training for this course, please contact us to make arrangements.

Devstral and Mistral models are open-source AI technologies designed for flexible deployment, fine-tuning, and scalable integration.

This instructor-led, live training (online or onsite) is aimed at intermediate–level to advanced–level ML engineers, platform teams, and research engineers who wish to self-host, fine-tune, and govern Mistral and Devstral models in 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 is a framework designed for constructing stateful, multi-agent LLM applications by composing graphs that maintain persistent state and allow precise control over execution flow.

This instructor-led training, available both online and on-site, is tailored for intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance.

Upon completion of this training, participants will be equipped to:

• Design financial LangGraph workflows that align 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 SLAs.

Course Format

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

Course Customization Options

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

LangGraph is a framework for constructing LLM applications with a graph structure, supporting planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (available online or onsite) is designed for beginner-level developers, prompt engineers, and data practitioners aiming to design and build reliable, multi-step LLM workflows using LangGraph.

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 apps 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.

LangGraph facilitates stateful, multi-actor 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 integrate seamlessly with medical workflows.

This instructor-led, live training session (available online or onsite) targets intermediate to advanced professionals aiming to design, implement, and manage LangGraph-based healthcare solutions while addressing regulatory, ethical, and operational challenges.

Upon completion of this training, participants will be able to:

• Design healthcare-specific LangGraph workflows with a focus on compliance and auditability.
• 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 within healthcare production settings.

Format of the Course

• Interactive lectures and discussions.
• Hands-on exercises using real-world case studies.
• Implementation practice in a live-lab environment.

Course Customization Options

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

LangGraph serves as a framework for constructing stateful, multi-agent LLM applications as composable graphs, featuring persistent state and precise execution control.

This instructor-led, live training (available online or onsite) targets intermediate to advanced professionals seeking to design, implement, and manage LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.

Upon completing this training, participants will be capable of:

• Designing 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 with observability and cost controls.

Course Format

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

Customization Options

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

LangGraph serves as a framework designed for composing graph-structured LLM workflows that support branching, tool use, memory, and controllable execution.

This instructor-led, live training (available online or onsite) targets intermediate-level engineers and product teams who wish to combine LangGraph’s graph logic with LLM agent loops to build dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

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

• Design graph-based workflows that coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallbacks for robust execution.
• Integrate retrieval, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and harden agent behavior for reliability and safety.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based design exercises and peer reviews.

Course Customization Options

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

LangGraph 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 live training, led by an instructor and available either online or onsite, targets intermediate-level marketers, content strategists, and automation developers who aim to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completion of this training, participants will be capable of:

• Designing graph-structured content and email workflows utilizing conditional logic.
• Integrating LLMs, APIs, and data sources to enable automated personalization.
• Managing state, memory, and context across multi-step campaigns.
• Evaluating, monitoring, and optimizing workflow performance and delivery outcomes.

Course Format

• Interactive lectures paired with group discussions.
• Practical labs focused on implementing email workflows and content pipelines.
• Scenario-based exercises covering personalization, segmentation, and branching logic.

Customization Options

• For a customized training session tailored to your needs, please get in touch with us to arrange it.

Le Chat Enterprise is a private ChatOps solution that offers secure, customizable, and governed conversational AI capabilities for organizations, supporting RBAC, SSO, connectors, and enterprise app integrations.

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.

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 admin playbooks for ChatOps.

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 comprises a family of high-performance large language models specifically optimized for scalable and cost-effective deployment in production environments.

This instructor-led training session, available both online and onsite, targets advanced infrastructure engineers, cloud architects, and MLOps leads who aim to design, deploy, and optimize Mistral-based architectures to achieve maximum throughput with minimal cost.

Upon completion of this training, participants will be capable of:

• Implementing scalable deployment patterns for Mistral Medium 3.
• Applying batching, quantization, and efficient serving strategies.
• 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 application.
• Hands-on implementation within a live-lab environment.

Customization Options

• To request customized training for this course, please contact us to make arrangements.

Mistral AI serves as an open-source AI platform, empowering teams to construct and embed conversational assistants within both enterprise operations and customer-facing processes.

This instructor-led live training, available either online or onsite, is tailored for beginner to intermediate product managers, full-stack developers, and integration engineers aiming to design, integrate, and scale conversational assistants using Mistral’s connectors and integrations.

Upon completing this training, participants will be capable of:

• Connecting Mistral conversational models with enterprise and SaaS connectors.
• Implementing retrieval-augmented generation (RAG) to ensure grounded, accurate responses.
• Designing UX patterns suitable for both internal and external chat assistants.
• Deploying assistants into real-world product workflows.

Course Format

• Interactive lectures and discussions.
• Practical integration exercises.
• Live-lab development of conversational assistants.

Customization Options

• For customized training arrangements, please contact us.

Mistral 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 AI offers an open, enterprise-ready AI platform equipped with features designed to facilitate secure, compliant, and responsible AI deployment.

This instructor-led live training, available online or onsite, targets intermediate-level compliance leads, security architects, and legal/operations stakeholders who aim to implement responsible AI practices using Mistral by leveraging privacy, data residency, and enterprise control mechanisms.

Upon completion of this training, participants will be able to:

• Implement privacy-preserving techniques in Mistral deployments.
• Apply data residency strategies to meet regulatory requirements.
• Set up enterprise-grade controls such as RBAC, SSO, and audit logs.
• Evaluate vendor and deployment options for compliance alignment.

Course Format

• Interactive lecture and discussion.
• Compliance-focused case studies and exercises.
• Hands-on implementation of enterprise AI controls.

Course Customization Options

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

Target Audience

Course Format

Upon completing this training, participants will be capable of:

In this instructor-led, live training session, attendees will acquire the skills to manipulate and visualize data using the tools provided within the Tidyverse.

The Tidyverse comprises a suite of flexible R packages designed for data cleaning, processing, modeling, and visualization. Key packages include: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Individuals new to the R programming language
• Those new to data analysis and visualization techniques

• A blend of lectures, discussions, exercises, and extensive practical, hands-on practice

• Execute data analysis and produce compelling visualizations
• Derive meaningful insights from various sample datasets
• Filter, sort, and summarize data to address exploratory questions
• Convert processed data into informative line charts, bar charts, histograms, and other plots
• Import and filter data from diverse sources, such as Excel, CSV, and SPSS files