Agentic AI Training in Christchurch

Generative AI and Agentic AI are two powerful paradigms driving the next wave of automation and intelligence — one focused on content generation and the other on goal-driven, autonomous behaviour.

This instructor-led, live training (online or on-site) is aimed at intermediate-level AI and technical professionals who wish to understand how to build, evaluate, and integrate generative and agentic AI into real-world applications.

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

• Understand the architecture and capabilities of generative AI systems.
• Explore the rise of autonomous AI agents and how they extend LLMs.
• Use prompt engineering and tool integrations for practical deployments.
• Compare models, tools, and techniques for responsible deployment.

Format of the Course

• Interactive lecture and discussion.
• Hands-on use of generative and agentic AI tools in real-world scenarios.
• Guided exercises focused on content generation and autonomous workflows.

Course Customisation Options

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

Agentic AI represents an emerging class of systems capable of autonomous decision-making, task execution, and workflow orchestration.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals seeking to understand how agentic AI will reshape organisational workflows, talent strategies, and job design.

Upon completing the course, participants will be able to:

• Evaluate the capabilities and limitations of agentic AI in enterprise settings.
• Identify opportunities for task automation, augmentation, and redesign.
• Assess workforce implications and develop responsible adoption strategies.
• Plan governance frameworks for safe, transparent, and compliant AI deployment.

Course Format

• Interactive lectures and discussions.
• Practical exercises and scenario-based analysis.
• Hands-on exploration of agentic workflows in a guided environment.

Course Customisation Options

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

The Hands-On Agentic AI Bootcamp is an intensive, project-driven course designed to help participants gain practical experience in designing, building, and deploying autonomous AI agents using Python. Through five progressively complex projects, participants will explore agentic design patterns, prompt workflows, API orchestration, and real-world integration scenarios.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to move rapidly from theory to implementation by developing working prototypes of agentic AI applications.

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

• Understand agentic AI architectures and key design principles.
• Develop, test, and deploy multiple agent-based applications in Python.
• Integrate agents with external tools, APIs, and databases.
• Optimise prompts and workflows for performance and reliability.
• Apply best practices for monitoring, versioning, and scaling agent systems.

Format of the Course

• Interactive lecture and guided coding sessions.
• Hands-on project development and debugging.
• Live demonstration of end-to-end agent deployment.

Course Customisation Options

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

Edge & Lightweight Agents is a hands-on course dedicated to deploying agentic AI workloads on resource-constrained devices. Participants will learn to build, optimise, and manage lightweight agents capable of local reasoning and inference, thereby enhancing speed, privacy, and reliability within distributed environments. The course places a strong emphasis on performance tuning, low-latency design, and the integration of hardware and software.

This instructor-led, live training (available online or on-site) is tailored for intermediate-level professionals who wish to implement and optimise on-device agentic systems using Python and edge AI frameworks.

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

• Understand the architecture and challenges associated with running agentic AI on edge devices.
• Design lightweight agent loops suitable for constrained environments.
• Implement local inference using TensorFlow Lite, PyTorch Mobile, and ONNX.
• Integrate agents with sensors, actuators, and IoT platforms.
• Optimise performance, energy consumption, and latency for real-time operation.

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on development in local or emulated environments.
• Project-based learning supported by guided implementation exercises.

Course Customisation Options

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

Agentic AI refers to systems that act autonomously to achieve goals, integrating reasoning, memory, and tool use. This course provides a structured introduction to agentic AI concepts, focusing on prompt engineering, architectural design patterns, and responsible use practices. Participants will gain foundational knowledge for building, guiding, and deploying agents effectively and safely.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level professionals who wish to understand how to design, prompt, and manage responsible agentic systems using practical frameworks and examples.

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

• Explain the core principles and lifecycle of agentic AI systems.
• Apply prompt engineering techniques for effective task completion.
• Design simple agent workflows using tool access and decision logic.
• Implement safety, governance, and responsible-use considerations in AI agents.
• Build a prototype agent using open frameworks and Python.

Course Format

• Interactive lectures and guided demonstrations.
• Hands-on exercises and coding practice.
• Collaborative discussions and case-based activities.

Course Customisation Options

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

Agentic AI for Business Automation is a hands-on course designed to teach participants how to design, integrate, and scale AI-driven agents for real-world business processes. The course focuses on mapping automation opportunities, integrating tools, and building practical use cases across customer service, supply chain, and marketing workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement AI-powered automation using no-code, low-code, and Python-based approaches.

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

• Identify key areas where agentic AI can drive process efficiency and innovation.
• Map workflows suitable for AI agent integration.
• Implement automation through APIs and orchestration tools.
• Integrate AI models into real business scenarios with measurable impact.
• Develop governance and monitoring structures for AI-driven operations.

Course Format

• Interactive lectures and practical demonstrations.
• Hands-on exercises and guided projects.
• Live implementation in a sandbox automation environment.

Course Customisation Options

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

This course explores the design, coordination, and implementation of multi-agent systems (MAS) using Python. Participants will learn how to build agents that communicate, collaborate, and adapt to achieve shared objectives in complex, dynamic environments.

This instructor-led, live training (online or on-site) is aimed at advanced-level professionals who wish to design and implement multi-agent systems for intelligent automation, simulation, and decision-making applications.

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

• Understand the architecture and principles of multi-agent systems.
• Develop agents capable of communication, coordination, and negotiation.
• Implement distributed environments for agent interactions.
• Apply reinforcement learning and planning in multi-agent contexts.
• Simulate cooperative and competitive agent behaviours.
• Design hybrid workflows combining humans and intelligent agents.

Course Format

• Instructor-led lectures and live demonstrations.
• Hands-on exercises using open-source agent frameworks.
• An applied group project simulating a multi-agent scenario.

Course Customisation Options

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

This course delves into the principles and practical implementation of reinforcement learning (RL) and sequential decision-making within agentic AI systems. Participants will learn how to design, train, and evaluate agents that interact dynamically with their environments to achieve long-term objectives through continuous learning and adaptation.

This instructor-led, live training (available online or on-site) is tailored for advanced-level engineers and researchers who aim to integrate reinforcement learning and planning algorithms into agentic systems for automation, robotics, and adaptive reasoning.

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

• Grasp the mathematical foundations underpinning reinforcement learning and decision-making.
• Implement key RL algorithms, including DQN, PPO, and A3C, using Python and PyTorch.
• Model environments with OpenAI Gym and design custom simulation scenarios.
• Train, evaluate, and debug agents for both continuous and discrete control tasks.
• Apply reinforcement learning techniques to real-world agentic AI use cases in robotics and planning.
• Strike a balance between exploration, exploitation, and safety constraints during real-world deployment.

Course Format

• Instructor-led lectures accompanied by live coding demonstrations.
• Hands-on exercises leveraging open-source frameworks and simulation environments.
• A practical project integrating decision-making capabilities into an agentic AI system.

Course Customisation Options

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

This course focuses on scaling, operationalising, and managing agentic AI systems in production environments, emphasising reliability, observability, and cost efficiency.

This instructor-led, live training (online or on-site) is aimed at advanced-level professionals who wish to build resilient, observable, and cost-optimised pipelines for large-scale agentic systems.

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

• Design scalable architectures for agentic AI workloads.
• Implement observability and monitoring frameworks tailored for agent behaviour and interactions.
• Apply performance tuning and resource optimisation techniques for long-running agent processes.
• Control costs and prevent “agent sprawl” through policy, orchestration, and automation.
• Integrate MLOps best practices for continuous deployment, versioning, and rollback of agentic services.

Format of the Course

• Hands-on, engineering-focused sessions with live infrastructure examples.
• Interactive discussion of architectural trade-offs and observability challenges.
• Capstone exercise: deploy and monitor a cost-controlled, production-grade agentic system.

Course Customisation Options

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

WrenAI enables organisations to move beyond static dashboards toward conversational analytics and embedded generative BI. This transition requires careful adoption planning, migration of assets, and effective change management practices.

This instructor-led, live training (online or onsite) is aimed at intermediate-level BI and data platform professionals who wish to modernise legacy BI systems with WrenAI.

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

• Evaluate legacy BI environments and identify modernisation opportunities.
• Plan and execute migrations from static dashboards to WrenAI.
• Adopt conversational analytics and embedded GenBI capabilities.
• Lead organisational change management for BI modernisation.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises with migration and adoption planning.
• Practical labs on conversational analytics and embedded GenBI.

Course Customisation Options

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

This course covers governance, identity management, and adversarial testing for agentic AI systems, with a focus on enterprise-safe deployment patterns and practical red-teaming techniques.

This instructor-led, live training (available online or on-site) is designed for advanced-level practitioners who wish to design, secure, and evaluate agent-based AI systems in production environments.

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

• Define governance models and policies for safe agentic AI deployments.
• Design non-human identity and authentication flows for agents with least-privilege access.
• Implement access controls, audit trails, and observability tailored to autonomous agents.
• Plan and execute red-team exercises to uncover misuses, escalation paths, and data exfiltration risks.
• Mitigate common threats to agentic systems through policy, engineering controls, and monitoring.

Format of the Course

• Interactive lectures and threat-modelling workshops.
• Hands-on labs: identity provisioning, policy enforcement, and adversary simulation.
• Red-team/blue-team exercises and end-of-course assessment.

Course Customisation Options

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

Python is the core language powering the development and orchestration of autonomous AI agents. This course focuses on practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to build, connect, and manage agent workflows.

This instructor-led, live training (available online or on-site) is designed for intermediate-level backend engineers, platform engineers, and ML engineers who wish to implement and orchestrate autonomous agents using Python tooling and APIs.

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

• Set up and configure Python-based environments for agentic systems.
• Use popular agent SDKs like LangChain and AutoGen to create functional agents.
• Integrate tools and APIs to extend agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on programming exercises and live demos.
• Practical projects building end-to-end agent workflows.

Course Customisation Options

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

WrenAI empowers finance teams to model key performance indicators (KPIs), integrate standardised metrics, and design dashboards that align with regulatory requirements and audit standards.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level finance professionals seeking to leverage WrenAI to build compliant financial data models and dashboards that support strategic decision-making and risk management.

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

• Model financial KPIs and metrics using WrenAI.
• Develop dashboards that meet regulatory and audit requirements.
• Integrate WrenAI with finance data sources for real-time reporting.
• Apply best practices in financial analytics and risk monitoring.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises using financial data models.
• Practical labs focused on dashboard design and compliance reporting.

Course Customisation Options

• To request a customised version of this training, please contact us to arrange.

This course teaches practical engineering techniques to design, build, test, and deploy agentic (autonomous) systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced-level ML engineers, AI developers, and software engineers who wish to build robust, production-ready autonomous agents using Python.

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

• Design and implement the agent loop and decision-making workflows.
• Integrate external tools and APIs to extend agent capabilities.
• Implement short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and agent composability.
• Apply safety, access control, and observability best practices for deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs building agents with Python and popular SDKs.
• Project-based exercises that produce deployable prototypes.

Course Customisation Options

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

WrenAI enables natural language to SQL generation and AI-powered analytics, making data access faster and more intuitive. For enterprise-grade use, quality assurance and observability practices are essential to ensure accuracy, reliability, and compliance.

This instructor-led, live training (online or onsite) is aimed at advanced-level data and analytics professionals who wish to evaluate query accuracy, apply prompt tuning, and implement observability practices for monitoring WrenAI in production.

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

• Evaluate the accuracy and reliability of NL to SQL outputs.
• Apply prompt tuning techniques to improve performance.
• Monitor drift and query behaviour across time.
• Instrument WrenAI with logging and observability frameworks.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises with evaluation and tuning techniques.
• Practical labs on observability and monitoring integrations.

Course Customisation Options

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

Agentic AI is an approach where AI systems plan, reason, and take tool-using actions to accomplish goals within defined constraints.

This instructor-led, live training (online or onsite) is aimed at intermediate-level healthcare and data teams who wish to design, evaluate, and govern agentic AI solutions for clinical and operational use cases.

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

• Explain agentic AI concepts and constraints in healthcare contexts.
• Design safe agent workflows with planning, memory, and tool usage.
• Build retrieval-augmented agents over clinical documents and knowledge bases.
• Evaluate, monitor, and govern agent behaviour with guardrails and human-in-the-loop controls.

Format of the Course

• Interactive lecture and facilitated discussion.
• Guided labs and code walkthroughs in a sandbox environment.
• Scenario-based exercises on safety, evaluation, and governance.

Course Customisation Options

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

WrenAI is an AI-powered analytics platform designed to connect data, model insights, and generate dashboards. In enterprise environments, robust governance and security are critical to ensuring safe and compliant adoption.

This instructor-led, live training (online or on-site) is aimed at advanced-level enterprise professionals who wish to implement governance, compliance, and security patterns for WrenAI at scale.

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

• Design and implement permissioning models in WrenAI.
• Apply auditability and monitoring practices for compliance.
• Set up secure environments with enterprise-level controls.
• Roll out WrenAI safely across large organisations.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focused on governance and security configurations.
• Practical exercises simulating enterprise rollout scenarios.

Course Customisation Options

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

This instructor-led, live training in Christchurch (online or on-site) is designed for intermediate-level AI developers and automation specialists who wish to integrate agentic capabilities into AI-powered applications.

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

• Grasp the core principles of agentic AI and autonomous decision-making.
• Implement goal-driven AI agents using self-optimisation techniques.
• Integrate multi-agent collaboration to tackle complex problem-solving challenges.
• Enhance AI-human interaction through adaptive user experiences.
• Deploy agentic AI models in real-world applications.

WrenAI Spreadsheets and the Metrics Library enable rapid reporting through AI-driven spreadsheet workflows and a comprehensive collection of pre-built, cross-platform business metrics.

This instructor-led, live training (available online or on-site) is designed for operations professionals at beginner to intermediate levels who aim to accelerate their reporting and analysis capabilities using WrenAI Spreadsheets and the Metrics Library.

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

• Construct AI-powered spreadsheets for data analysis and reporting.
• Utilise the WrenAI Metrics Library for standardised KPIs.
• Connect spreadsheets to multiple data sources to enable live updates.
• Develop automated workflows to streamline operational reporting.

Course Format

• Interactive lectures and discussions.
• Hands-on spreadsheet development using WrenAI.
• Practical exercises focused on metrics and KPI reporting.

Course Customisation Options

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

This instructor-led, live training in Christchurch (available online or on-site) is designed for advanced-level professionals seeking to develop and optimise multi-agent systems using Agentic AI frameworks.

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

• Grasp the core principles of Agentic AI within multi-agent environments.
• Develop AI-driven agents capable of autonomous interaction.
• Implement reinforcement learning to foster adaptive AI behaviour.
• Optimise both collaboration and competition among multiple agents.
• Apply Agentic AI across robotics, gaming, and enterprise automation.

The WrenAI API provides a powerful interface for generating SQL queries from natural language, developing custom applications, and integrating charts into internal platforms.

This instructor-led, live training (available online or on-site) is designed for intermediate-level engineers who want to leverage the WrenAI API for practical use cases, including SQL generation, data visualisation, and application integration.

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

• Authenticate and connect applications to the WrenAI API.
• Generate SQL queries from natural language inputs.
• Create and embed charts using API endpoints.
• Integrate WrenAI into backend systems and internal tools.

Course Format

• Interactive lectures and discussion sessions.
• Hands-on exercises involving API calls and integrations.
• Practical projects that connect applications, charts, and data pipelines.

Course Customisation Options

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

This instructor-led, live training in Christchurch (available online or on-site) is designed for advanced-level professionals seeking to harness Agentic AI for enterprise-scale automation and strategic AI adoption.

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

• Grasp the role of Agentic AI within enterprise applications.
• Integrate autonomous AI agents with enterprise systems.
• Optimise AI-driven workflows for scalability and efficiency.
• Ensure compliance, security, and governance in AI automation.
• Develop AI-driven business strategies to support digital transformation.

WrenAI Cloud is a modern platform for connecting data sources, modelling data, and building interactive dashboards.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level data professionals who wish to learn how to set up WrenAI Cloud, model data, and visualise insights in dashboards.

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

• Set up and configure WrenAI Cloud environments.
• Connect WrenAI Cloud to multiple data sources.
• Model data and define relationships for analytics.
• Create interactive dashboards for business insights.

Format of the Course

• Interactive lecture and discussion.
• Hands-on cloud platform configuration and data modelling.
• Practical exercises in dashboard building and visualisation.

Course Customisation Options

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

This instructor-led, live training in Christchurch (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for decision-making in complex business and technical scenarios.

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

• Understand the principles of autonomous decision-making in AI.
• Design and implement AI agents that operate with minimal human intervention.
• Integrate Agentic AI into automation workflows and business systems.
• Optimize AI-driven decision processes for efficiency and scalability.
• Ensure compliance, security, and ethical considerations in AI autonomy.

WrenAI is an open-source generative BI tool that enables natural language to SQL conversion and semantic data modelling.

This instructor-led, live training (online or on-site) is aimed at advanced-level data engineers, analytics engineers, and ML engineers who wish to build robust semantic layers, tune prompts, and ensure reliable SQL generation.

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

• Implement semantic models for consistent metric definitions across teams.
• Optimise text-to-SQL performance for accuracy and scalability.
• Configure and enforce guardrails to avoid invalid or risky queries.
• Integrate WrenAI OSS into data pipelines and analytics workflows.

Course Format

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

Course Customisation Options

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

This instructor-led, live training in Christchurch (online or onsite) is designed for intermediate-level AI engineers, ML researchers, and developers who wish to build and implement Agentic AI systems in real-world applications.

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

• Understand the core principles of Agentic AI systems.
• Implement AI agents capable of autonomous reasoning and action.
• Integrate Agentic AI with APIs and third-party services.
• Optimise multi-agent interactions for complex tasks.
• Address ethical, security, and scalability challenges in Agentic AI.

WrenAI empowers SaaS providers to embed generative business intelligence (GenBI) directly into their customer-facing products. This course equips SaaS teams with the practical skills needed to integrate WrenAI via its Embedded API, configure white-label analytics, and manage multi-tenant deployments.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level SaaS product leaders, data engineers, and full-stack developers who aim to deploy WrenAI as an embedded analytics solution within SaaS environments.

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

• Integrate WrenAI using the Embedded API for customer-facing applications.
• Implement white-label conversational BI with full branding and customisation.
• Design secure and scalable multi-tenant deployments.
• Monitor usage, optimise performance, and ensure compliance in SaaS environments.

Format of the Course

• Interactive lectures and discussion.
• Hands-on labs using the WrenAI Embedded API.
• Workshop: design and deploy a white-label analytics feature tailored to a SaaS use case.

Course Customisation Options

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

This instructor-led, live training in Christchurch (available online or on-site) is designed for beginner-level professionals who wish to grasp the fundamental principles of Agentic AI, its capabilities, and its potential impact across industries.

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

• Understand the core principles of Agentic AI.
• Distinguish between traditional AI and autonomous AI agents.
• Explore real-world applications of Agentic AI across various industries.
• Evaluate the benefits and challenges of deploying autonomous AI systems.
• Analyse the ethical and security considerations associated with Agentic AI.

WrenAI is a conversational analytics platform that translates natural-language queries into reliable analytics, enabling non-technical teams to generate insights quickly and consistently.

This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, analysts, and data champions who wish to adopt conversational analytics and build self-service BI capabilities with WrenAI.

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

• Design conversational analytics workflows that surface reliable product insights.
• Create and maintain a standardised metrics layer for consistent reporting.
• Use natural-language to SQL features effectively to answer product questions.
• Embed WrenAI-driven self-service dashboards and guardrails in product workflows.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with Wren AI and sample datasets.
• Workshop: build a self-service dashboard and conversational query set.

Course Customisation Options

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

AI agents are transitioning from research demonstrations to autonomous production systems capable of operating across text, image, speech, and tool-driven workflows. This evolution demands higher standards for engineering rigour, adversarial robustness, and regulatory accountability. This instructor-led training guides advanced practitioners through the entire agent lifecycle, covering everything from architecting single and multi-agent systems to integrating multi-modal perception and orchestrating coordinated agent behaviour using modern frameworks. Through progressive hands-on labs in Python, participants will construct a production-grade multi-agent system, subsequently stress-testing it with adversarial techniques and the Adversarial Robustness Toolbox. The course concludes with alignment to NIST AI RMF, ISO/IEC 42001, the EU AI Act, and GDPR, alongside secure deployment, monitoring, and incident response strategies. By the end, participants will be equipped to deploy agents that are capable, defensible, and compliant.

This instructor-led, live training in Christchurch (available online or on-site) is designed for beginner to intermediate-level developers and cloud practitioners who wish to leverage Alibaba Cloud to build AI agents capable of automating tasks, answering questions, and integrating with business systems.

By the end of this training, participants will be able to: understand AI agent architecture on Alibaba Cloud, build a simple agent workflow, connect an agent to enterprise knowledge and tools, and deploy and monitor an agent within a cloud environment.