AI on Amazon Web Services (AWS) Training Course

LangGraph is a framework designed for constructing 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 aiming 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 for speed, cost-efficiency, and scalability.
• Ensure 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.

Course Format

• Interactive lecture and discussion.
• Ample 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 Nigeria (onsite or remote) is designed for engineers who want to deploy and manage IoT devices on AWS.

By the end of this training, participants will be able to build an IoT platform that includes the deployment and management of a backend, gateway, and devices on top of AWS.

This instructor-led live training in Nigeria (available online or onsite) is aimed at developers who wish to install, configure, and manage AWS IoT Greengrass capabilities to create applications for various devices.

By the end of this training, participants will be able to use AWS IoT Greengrass to build, deploy, manage, secure, and monitor applications on intelligent devices.

This instructor-led live training Nigeria (onsite or remote) is aimed at developers who wish to use AWS Lambda to build and deploy services and applications to the cloud, without needing to worry about provisioning the execution environment (servers, VMs and containers, availability, scalability, storage, etc.).

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

• Configure AWS Lambda to execute a function.
• Understand FaaS (Functions as a Service) and the advantages of serverless development.
• Build, upload and execute AWS Lambda functions.
• Integrate Lambda functions with different event sources.
• Package, deploy, monitor and troubleshoot Lambda based applications.

Devstral is an open-source framework engineered for creating and executing coding agents capable of interacting with code repositories, developer tools, and APIs to boost engineering productivity.

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

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

• Install 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 practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This instructor-led, live training in Nigeria (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for DevOps workflows.
• Implement continuous integration and continuous delivery (CI/CD) pipelines.
• Automate testing, monitoring, and deployment processes using AWS Cloud9.
• Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows.
• Utilize source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training in Nigeria (online or onsite) is designed for intermediate-level professionals who wish to learn how to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda.

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

• Understand the fundamentals of serverless architecture.
• Set up AWS Cloud9 for serverless application development.
• Develop, test, and deploy serverless applications using AWS Lambda.
• Integrate AWS Lambda with other AWS services such as API Gateway and S3.
• Optimize serverless applications for performance and cost efficiency.

This instructor-led, live training in Nigeria (online or onsite) is aimed at beginner to intermediate researchers and laboratory professionals who want to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.

Upon completing this training, participants will be able to:

• Navigate the Fiji interface and make effective use of ImageJ’s core functions.
• Preprocess and enhance scientific images to improve analysis outcomes.
• Perform quantitative image analysis, including cell counting and area measurement.
• Automate repetitive tasks using macros and plugins.
• Customize workflows to meet specific image analysis requirements in biological research.

Summary:

• Gaining an understanding of IoT architecture and its core functionalities.
• Exploring the concepts of 'Things' and 'Sensors', the Internet of Things, and mapping business processes to IoT solutions.
• Reviewing IoT software components comprehensively: hardware, firmware, middleware, cloud infrastructure, and mobile applications.
• Examining key IoT functions: fleet management, data visualization, SaaS-based Facility Management (FM) and Data Visualization (DV), alerting/alarm systems, sensor and 'thing' onboarding, and geo-fencing.
• Learning the fundamentals of IoT device-to-cloud communication using MQTT.
• Connecting IoT devices to AWS via MQTT using AWS IoT Core.
• Integrating AWS IoT Core with AWS Lambda for computation and Amazon DynamoDB for data storage.
• Linking a Raspberry Pi to AWS IoT Core for seamless data communication.
• Practical lab session: Building a smart device using a Raspberry Pi and AWS IoT Core.
• Visualizing sensor data and managing web interface communication.

LangGraph is a framework designed for constructing stateful, multi-actor LLM applications as composable graphs with persistent state and 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 finance solutions with proper governance, observability, and compliance.

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

• Design finance-specific LangGraph workflows aligned to 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.

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 is a framework for building graph-structured LLM applications that support planning, branching, tool use, memory, and controllable execution.

This instructor-led, live training (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.

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 empowers the creation of stateful, multi-actor workflows driven by LLMs, offering precise control over execution paths and state persistence. In the healthcare sector, these capabilities are vital for ensuring compliance, interoperability, and the development of decision-support systems that seamlessly align with clinical workflows.

This instructor-led live training, available online or on-site, targets intermediate to advanced professionals eager to design, implement, and manage LangGraph-based healthcare solutions. The course addresses the regulatory, ethical, and operational challenges inherent in this field.

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

• Designing healthcare-specific LangGraph workflows that prioritise compliance and auditability.
• Integrating LangGraph applications with medical ontologies and standards such as FHIR, SNOMED CT, and ICD.
• Applying best practices for reliability, traceability, and explainability within sensitive environments.
• Deploying, monitoring, and validating LangGraph applications in healthcare production settings.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises grounded in real-world case studies.
• Practical implementation within a live laboratory environment.

Customisation Options

• To arrange a tailored training session for this course, please get in touch with us.

LangGraph serves as a framework for constructing stateful, multi-actor LLM applications by composing them into graphs that maintain persistent state and offer precise control over execution.

This instructor-led live training, available either online or onsite, is designed for intermediate to advanced professionals seeking to design, implement, and operate LangGraph-based legal solutions with the necessary compliance, traceability, and governance controls.

Upon completing 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.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation 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 designed for creating graph-structured LLM workflows that accommodate branching, tool integration, 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 such as 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 processes, APIs, and structured outputs into agent loops.
• Evaluate, monitor, and secure agent behaviour 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 is a graph-based orchestration framework that empowers conditional, multi-step LLM and tool workflows, making it ideal for automating and personalising 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 personalisation.
• Manage state, memory, and context across multi-step campaigns.
• Evaluate, monitor, and optimise 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 personalisation, segmentation, and branching logic.

Course Customization Options

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