NLP: Natural Language Processing with R Training Course

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

This instructor-led, live training (available online or onsite) targets advanced-level AI platform engineers, AI DevOps specialists, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.

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

• Design and optimize complex LangGraph topologies for speed, cost efficiency, and scalability.
• Enhance 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.
• 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 specifically crafted for creating and operating coding agents. These agents can interact with codebases, developer tools, and APIs to significantly boost engineering productivity.

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

Upon completing this training, participants will be able to:

• Set up and configure Devstral for coding agent development.
• Design agentic workflows for exploring and modifying codebases.
• Integrate coding agents with developer tools and APIs.
• Implement 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 customized training for this course, please contact us to arrange.

Devstral 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 machine learning 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 serves as a framework designed for constructing stateful, multi-agent LLM applications through composable graphs that maintain persistent state and precise execution control.

This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals looking to design, implement, and operate LangGraph-based financial solutions that ensure proper governance, observability, and compliance.

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

• Designing finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrating financial data standards and ontologies into graph states and tooling.
• Implementing reliability, safety, and human-in-the-loop controls for critical processes.
• Deploying, monitoring, and optimizing LangGraph systems to achieve desired performance, cost efficiency, and SLAs.

Course Format

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

Customization Options

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

LangGraph serves as a framework for constructing graph-structured LLM applications that facilitate planning, branching, tool utilization, memory management, and controllable execution.

This instructor-led live training, available both online and on-site, targets beginner-level developers, prompt engineers, and data practitioners who aim to design and implement reliable, multi-step LLM workflows using LangGraph.

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

• Articulate core LangGraph concepts (nodes, edges, state) and understand their appropriate use cases.
• Construct prompt chains capable of branching, invoking tools, and maintaining memory.
• 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 coupled with facilitated discussions.
• Guided laboratory sessions and code walkthroughs within a sandbox environment.
• Scenario-based exercises focusing on design, testing, and evaluation.

Customization Options

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

LangGraph facilitates stateful, multi-agent workflows driven by Large Language Models (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 seamlessly align with medical workflows.

This instructor-led training, available both online and on-site, targets intermediate to advanced professionals seeking to design, implement, and manage healthcare solutions using LangGraph, while addressing regulatory, ethical, and operational challenges.

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

• Design healthcare-specific LangGraph workflows that prioritize compliance and auditability.
• Integrate LangGraph applications with medical ontologies and standards, including FHIR, SNOMED CT, and ICD.
• Apply best practices for reliability, traceability, and explainability in sensitive environments.
• Deploy, monitor, and validate LangGraph applications within healthcare production settings.

Course Format

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

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 through composable graphs that maintain persistent state and offer precise execution control.

This instructor-led live training (available online or onsite) is designed for intermediate to advanced professionals aiming to design, implement, and operate LangGraph-based legal solutions with essential 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 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 designed for composing graph-structured workflows involving Large Language Models (LLMs) that facilitate branching, tool utilization, memory management, and controlled execution.

This instructor-led live training, available online or onsite, targets intermediate-level engineers and product teams looking to merge LangGraph’s graph logic with LLM agent loops. The goal is to develop dynamic, context-aware applications such as customer support agents, decision trees, and information retrieval systems.

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

• Design graph-based workflows that effectively coordinate LLM agents, tools, and memory.
• Implement conditional routing, retries, and fallback mechanisms to ensure robust execution.
• Integrate retrieval processes, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and enhance agent behavior to ensure reliability and safety.

Course Format

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

Customization Options

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

LangGraph is a graph-based orchestration framework that enables conditional, multi-step LLM and tool workflows, ideal for automating and personalizing content pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level marketers, content strategists, and automation developers who wish to implement dynamic, branching email campaigns and content generation pipelines using LangGraph.

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

• Design graph-structured content and email workflows with conditional logic.
• Integrate LLMs, APIs, and data sources for automated personalization.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimize workflow performance and delivery outcomes.

Format of the Course

• Interactive lectures and group discussions.
• Hands-on labs implementing email workflows and content pipelines.
• Scenario-based exercises on personalization, segmentation, and branching logic.

Course Customization Options

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

Le Chat Enterprise delivers a secure, customizable, and governed ChatOps solution, empowering organizations with conversational AI capabilities while supporting RBAC, SSO, connectors, and enterprise application integrations.

This instructor-led live training, available both online and onsite, is designed for intermediate-level product managers, IT leads, solution engineers, and security or compliance teams looking to deploy, configure, and govern Le Chat Enterprise within their enterprise environments.

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

• Deploy and configure Le Chat Enterprise for secure operations.
• Implement RBAC, SSO, and compliance-oriented controls.
• Connect Le Chat Enterprise with enterprise applications and data repositories.
• Create and execute governance and administrative playbooks for ChatOps.

Course Format

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

Customization Options

• For tailored training requests, please contact us to arrange.

Mistral represents a high-performance lineage of large language models specifically optimized for cost-efficient production deployment at scale.

This instructor-led live training, available online or on-site, is designed for advanced-level infrastructure engineers, cloud architects, and MLOps leaders who aim to design, deploy, and refine Mistral-based architectures to achieve maximum throughput while minimizing costs.

Upon completing 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 suitable for enterprise workloads.

Format of the Course

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

Course Customization Options

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

Mistral AI provides an open-source AI platform that empowers teams to create and embed conversational assistants within enterprise environments and customer-facing processes.

This instructor-led live training, available online or on-site, targets beginner to intermediate product managers, full-stack developers, and integration engineers looking to design, integrate, and commercialize conversational assistants via Mistral connectors and integrations.

Upon completing this training, participants will be able to:

• Connect Mistral conversational models with enterprise and SaaS connectors.
• Implement retrieval-augmented generation (RAG) to ensure grounded responses.
• Create UX patterns for both internal and external chat assistants.
• Deploy assistants into product workflows for practical use cases.

Course Format

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

Customization Options

• To request a customized version of this course, please contact us to arrange it.

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 serves as an open, enterprise-grade AI platform offering capabilities for the secure, compliant, and responsible deployment of artificial intelligence.

This instructor-led training session, available both online and on-site, is designed for compliance leads, security architects, and legal and operations stakeholders at an intermediate level. The course focuses on implementing responsible AI practices using Mistral by leveraging privacy protections, data residency controls, and enterprise management mechanisms.

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

• Deploy privacy-preserving techniques within Mistral environments.
• Execute data residency strategies to satisfy regulatory obligations.
• Establish enterprise-grade controls, including RBAC, SSO, and audit logging.
• Assess vendor and deployment alternatives to ensure compliance alignment.

Course Format

• Interactive lectures and discussions.
• Case studies and exercises centered on compliance.
• Practical implementation of enterprise AI controls.

Customization Options

• For tailored training on this subject, please contact us to make arrangements.

Audience

Format of the course

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

In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.

The Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.

• Beginners to the R language
• Beginners to data analysis and data visualization

• Part lecture, part discussion, exercises and heavy hands-on practice

• Perform data analysis and create appealing visualizations
• Draw useful conclusions from various datasets of sample data
• Filter, sort and summarize data to answer exploratory questions
• Turn processed data into informative line plots, bar plots, histograms
• Import and filter data from diverse data sources, including Excel, CSV, and SPSS files