Natural Language Processing (NLP) - AI/Robotics Training Course

Drones and photogrammetry have become indispensable tools in high-precision infrastructure supervision. By integrating advanced geodesy principles, real-time modeling, and high-accuracy drone mapping, professionals can achieve deeper insights, greater accuracy, and enhanced productivity within construction environments.

This instructor-led live training, available both online and onsite, is designed for intermediate to advanced-level professionals who aim to apply sophisticated drone and photogrammetry workflows. These include geodetic controls and high-precision mapping techniques tailored to complex infrastructure projects.

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

• Implement advanced photogrammetric methods, such as RTK/PPK workflows and ground control calibration.
• Integrate geodetic reference systems and projections suitable for large-scale infrastructure sites.
• Design precision flight missions adapted to complex terrains and infrastructure geometries.
• Analyze photogrammetry data using GIS software to monitor structural health, deformation, and compliance.

Course Format

• Interactive lectures and discussions.
• Advanced exercises and real-world case studies.
• Hands-on implementation using drone data and modeling tools.

Course Customization Options

• For those interested in a customized training session, please contact us to make arrangements.

LangGraph serves as a robust framework designed for constructing stateful, multi-agent LLM applications through composable graphs, ensuring persistent state and precise control over execution flows.

This instructor-led live training, available both online and onsite, targets advanced AI platform engineers, DevOps professionals specializing in AI, and ML architects who aim to optimize, debug, monitor, and manage production-grade LangGraph systems.

Upon completing this training, participants will be equipped to:

• Design and optimize complex LangGraph topologies to enhance speed, reduce costs, and improve scalability.
• Ensure system reliability through the implementation of retries, timeouts, idempotency, and checkpoint-based recovery mechanisms.
• Debug and trace graph executions, inspect states, and systematically reproduce issues encountered in production environments.
• Instrument graphs with logs, metrics, and traces, deploy them to production, and actively monitor SLAs and associated costs.

Course Format

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

Customization Options

• For inquiries regarding customized training for this course, please contact us to make arrangements.

Devstral is an open-source framework engineered to build and operate coding agents capable of interacting with codebases, developer utilities, and APIs to 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 completion of this training, participants will be equipped 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.
• Apply 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 laboratory environment.

Course Customization Options

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

Devstral and Mistral are open-source artificial intelligence technologies engineered for flexible deployment, custom fine-tuning, and scalable integration.

This instructor-led live training, available either online or on-site, is designed for intermediate to advanced machine learning engineers, platform teams, and research engineers who aim to self-host, fine-tune, and govern Mistral and Devstral models within production environments.

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

• Establish and configure self-hosted environments tailored for Mistral and Devstral models.
• Apply fine-tuning techniques to enhance performance in specific domains.
• Implement version control, monitoring, and lifecycle governance mechanisms.
• Ensure security, regulatory compliance, and responsible utilization of open-source models.

Course Format

• Interactive lectures and discussions.
• Practical exercises focused on self-hosting and fine-tuning.
• Live laboratory sessions for implementing governance and monitoring pipelines.

Customization Options

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

Instructor-led, this live training (available online or onsite) is designed for beginner to intermediate participants aiming to learn how to apply drone and photogrammetry techniques for supervising construction infrastructure.

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

• Understand the fundamentals of drones and photogrammetry.
• Develop and execute drone flight plans for construction sites.
• Perform photogrammetry tracking and create detailed maps and 3D models.
• Use photogrammetry data for infrastructure supervision and issue detection.
• Apply drone technology to improve construction site safety and efficiency.

The Evo Max 4T is a professional-grade drone designed for advanced aerial operations, inspections, and data collection.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level operators who wish to safely and effectively use the Evo Max 4T for professional applications and prepare for official certification.

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

• Understand the technical specifications and operation of the Evo Max 4T drone.
• Apply operational safety procedures in aerial activities.
• Comply with current AAC and local drone regulations.
• Implement best practices for efficient and safe drone operations.
• Prepare for certification/licensing through theoretical and practical training.

Format of the Course

• Interactive lecture and discussion.
• Hands-on practice with drone equipment and simulators.
• Practical exercises and real flight scenarios.

Course Customization Options

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

LangGraph serves as a framework designed for creating stateful, multi-agent LLM applications through composable graphs that maintain persistent state and offer precise control over execution flow.

This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals looking to design, implement, and manage LangGraph-based financial solutions with robust governance, observability, and compliance measures.

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

• Design finance-specific LangGraph workflows that align with regulatory and audit requirements.
• Integrate financial data standards and ontologies into graph states and associated tooling.
• Implement reliability, safety, and human-in-the-loop controls for critical processes.
• Deploy, monitor, and optimize LangGraph systems to ensure optimal performance, cost-efficiency, and adherence to SLAs.

Course Format

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

Customization Options

• For customized training requests for this course, please contact us to arrange details.

LangGraph is a framework designed for constructing graph-structured LLM applications that facilitate planning, branching, tool use, memory management, and controllable execution.

This instructor-led, live training (available online or onsite) targets beginner-level developers, prompt engineers, and data practitioners who aim 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 LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are essential for ensuring compliance, enhancing interoperability, and developing decision-support systems that align with clinical workflows.

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

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

• Design healthcare-specific LangGraph workflows with a focus on 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.

Course Customization Options

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

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to design, implement, and operate LangGraph-based legal solutions 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 preserve 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.
• 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.

LangGraph serves as a framework for assembling graph-structured Large Language Model (LLM) workflows that enable branching, tool utilization, memory management, and controlled execution.

This instructor-led, live training session (available online or onsite) targets intermediate-level engineers and product teams aiming to merge LangGraph’s graph logic with LLM agent loops to develop dynamic, context-aware applications. Examples include customer support agents, decision trees, and information retrieval systems.

Upon completing 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 systems, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and strengthen agent behavior to guarantee reliability and safety.

Course Format

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

Course Customization Options

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

LangGraph serves as a graph-based orchestration framework designed to facilitate conditional, multi-step workflows involving Large Language Models (LLMs) and tools, making it ideal for automating and personalizing content pipelines.

This instructor-led live training, available both online and onsite, targets intermediate-level marketers, content strategists, and automation developers. The course focuses on implementing dynamic, branching email campaigns and content generation pipelines using LangGraph.

Upon completing this training, participants will be equipped to:

• Create graph-structured workflows for content and email, incorporating conditional logic.
• Seamlessly integrate LLMs, APIs, and data sources to enable automated personalization.
• Effectively manage state, memory, and context throughout multi-step campaigns.
• Evaluate, monitor, and optimize the performance and delivery outcomes of their workflows.

Course Format

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

Course Customization Options

• For those interested in tailored training for this course, please get in touch with us to make arrangements.

Hands-On Rapid Prototyping for Robotics Using ROS 2 & Docker is a practical course crafted to assist developers in efficiently building, testing, and deploying robotic applications. Participants will acquire skills in containerizing robotics environments, integrating ROS 2 packages, and prototyping modular robotic systems by leveraging Docker for enhanced reproducibility and scalability. The curriculum places strong emphasis on agility, version control, and collaborative practices ideal for innovation teams at the early stages of development.

This instructor-led live training, available both online and onsite, is tailored for participants at beginner to intermediate levels who aim to speed up their robotics development workflows through the use of ROS 2 and Docker.

Upon completing this training, participants will be capable of:

• Establishing a ROS 2 development environment within Docker containers.
• Developing and testing robotic prototypes within modular and reproducible setups.
• Utilizing simulation tools to validate system behaviour prior to hardware deployment.
• Collaborating effectively via containerized robotics projects.
• Applying continuous integration and deployment concepts within robotics pipelines.

Course Format

• Interactive lectures and demonstrations.
• Practical exercises involving ROS 2 and Docker environments.
• Mini-projects centred on real-world robotic applications.

Customization Options

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

In this instructor-led live training, participants will learn how to start using ROS for their robotics projects through the use of robotics visualization and simulation tools.

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

• Understand the basics of ROS.
• Learn how to create a basic robotics project using ROS.
• Learn how to use different tools for robotics including simulation and visualization tools.

This instructor-led live training in Kenya (online or onsite) is designed for beginner to intermediate robotics developers, and potentially advanced-level professionals, who wish to learn how to program mobile robots using ROS and Python.

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

• Set up a development environment that includes ROS, Python, and a mobile robot platform.
• Create and run ROS nodes, topics, services, and actions using Python.
• Use ROS tools and utilities to monitor and debug ROS applications.
• Use ROS packages and libraries to perform common tasks for mobile robots.
• Integrate ROS with other frameworks and tools.
• Troubleshooting and debugging ROS applications.