Large Language Models (LLMs) Training in Christchurch

This instructor-led, live training in Christchurch (available online or on-site) is designed for senior management professionals seeking to understand what LLMs are, explore their potential impact on business operations, and evaluate practical applications of AI tools such as ChatGPT, Microsoft Copilot, or Grok for real-world tasks including content creation, data summarisation, and decision support.

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

• Understand what LLMs are and how tools like ChatGPT and Copilot function.
• Apply prompt techniques to obtain practical, reliable results from LLMs.
• Evaluate real-world use cases such as email drafting, document summarisation, and productivity automation.
• Identify investment opportunities and strategic applications for AI adoption.

This instructor-led, live training in Christchurch (online or on-site) is aimed at senior management teams who wish to understand the strategic value of LLMs and enterprise AI tools. Participants will explore how to integrate these tools into high-level workflows, draft better prompts, and evaluate opportunities for increased productivity and ROI through AI adoption.

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

• Understand how LLMs function and how tools like ChatGPT and Copilot apply them.
• Use prompt-based interactions to automate and accelerate tasks.
• Apply AI tools to real scenarios such as email drafting, report summarisation, and agreement review.
• Evaluate strategic benefits, limitations, and licensing considerations for LLM adoption.

This instructor-led, live training in Christchurch (online or on-site) is aimed at intermediate-level to advanced-level AI researchers, data scientists, and developers who wish to understand, fine-tune, and implement Meta AI's Large Language Models for various NLP applications.

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

• Understand the architecture and functioning of Meta AI's Large Language Models.
• Set up and fine-tune Meta AI LLMs for specific use cases.
• Implement LLM-based applications such as text summarisation, chatbots, and sentiment analysis.
• Optimise and deploy large language models efficiently.

This instructor-led, live training in Christchurch (available online or on-site) is designed for intermediate-level AI professionals, business analysts, and technology leaders who wish to grasp the principles of generative AI and explore the practical applications of LLMs in business contexts. Participants will gain insights into transformers, prompt engineering, and the ethical considerations involved in deploying these models for real-world solutions.

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

• Understand the core principles underpinning generative AI and large language models.
• Implement and fine-tune LLMs for specific business use cases.
• Apply prompt engineering techniques to achieve optimal model outputs.
• Identify ethical considerations and effectively manage risks associated with LLM deployment.

This instructor-led, live training in Christchurch (online or on-site) is designed for intermediate-level AI professionals and ethicists, data scientists and engineers, as well as policy makers and stakeholders seeking to understand and navigate the ethical landscape of LLMs.

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

• Identify ethical issues and challenges associated with LLMs.
• Apply ethical frameworks and principles to the deployment of LLMs.
• Assess the societal impact of LLMs and mitigate potential risks.
• Develop strategies for responsible AI development and usage.

This instructor-led, live training in Christchurch (online or onsite) is aimed at intermediate-level NLP practitioners and data scientists, content creators and translators, and global businesses who wish to use LLMs for language translation and creating multilingual content.

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

• Understand the principles of cross-lingual learning and translation with LLMs.
• Implement LLMs for translating content between various languages.
• Create and manage multilingual datasets for training LLMs.
• Develop strategies for maintaining consistency and quality in translation.

This instructor-led, live training in Christchurch (delivered online or on-site) is designed for intermediate-level financial analysts, data scientists, and investment professionals who wish to leverage LLMs for financial market analysis and prediction.

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

• Understand the application of LLMs in financial market analysis.
• Use LLMs to process financial news, reports, and data for market insights.
• Develop predictive models for stock prices, market trends, and economic indicators.
• Integrate LLM insights into investment decision-making processes.

This instructor-led, live training in Christchurch (delivered online or on-site) is designed for intermediate-level environmental scientists and researchers, data analysts, and policy makers and environmental advocates who wish to leverage LLMs for environmental modelling and analysis.

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

• Understand the application of LLMs in environmental science.
• Utilise LLMs to analyse and model environmental data.
• Interpret LLM outputs for environmental impact assessments.
• Communicate findings effectively to inform policy and conservation efforts.

This instructor-led, live training in Christchurch (online or onsite) is designed for intermediate-level VR and AR developers, game designers, and AI engineers who aim to incorporate LLMs into VR and AR applications to create more engaging and responsive environments.

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

• Understand the role of LLMs in crafting immersive VR and AR experiences.
• Develop VR and AR applications that leverage LLMs for interactive dialogues and content creation.
• Integrate LLMs with VR and AR development tools to enhance user engagement.
• Apply best practices for designing AI-driven narratives and interactions within virtual spaces.

This instructor-led, live training in Christchurch (online or on-site) is designed for intermediate-level data scientists, machine learning engineers, and software developers seeking to apply Large Language Models (LLMs) to multimodal data for advanced AI use cases.

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

• Grasp the core principles of multimodal learning using LLMs.
• Implement LLMs to process and analyse text, image, and audio data.
• Develop applications that leverage the strengths of multimodal data integration.
• Evaluate the performance of multimodal LLM systems.

This instructor-led, live training in Christchurch (online or on-site) is designed for intermediate-level cybersecurity professionals and data scientists who wish to leverage LLMs to enhance cybersecurity defences and threat intelligence.

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

• Understand the role of LLMs in cybersecurity.
• Implement LLMs for threat detection and analysis.
• Utilise LLMs for security automation and response.
• Integrate LLMs with existing security infrastructure.

This instructor-led, live training in Christchurch (available online or on-site) is designed for intermediate-level data scientists and business analysts who want to leverage large language models (LLMs) to forecast trends and behaviours across various industries.

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

• Grasp the fundamentals of LLMs and their role in predictive analytics.
• Apply LLMs to analyse and forecast data across diverse industries.
• Assess the effectiveness of predictive models using LLMs.
• Integrate LLMs into existing data processing pipelines.

This instructor-led, live training in Christchurch (available online or on-site) is designed for intermediate-level data scientists who wish to gain a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

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

• Understand the components and functionality of transformer models.
• Optimise and fine-tune LLMs for specific tasks and applications.
• Grasp the core principles and methodologies of reinforcement learning.
• Learn how reinforcement learning techniques can enhance the performance of LLMs.

This instructor-led, live training in Christchurch (online or on-site) is designed for intermediate-level content creators, marketers, and educational technologists who want to harness the power of LLMs to generate high-quality, diverse, and engaging content across a range of domains.

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

• Understand the capabilities of LLMs and how they can be applied to content generation.
• Set up and use LLMs to create various types of content.
• Apply best practices for prompting and fine-tuning LLMs to produce desired outcomes.
• Evaluate the quality of AI-generated content and refine it for specific audiences.
• Explore advanced techniques for creative and multi-modal content generation using LLMs.

This instructor-led, live training in Christchurch (online or onsite) is designed for educators, EdTech professionals, and researchers at varying levels of experience and expertise who wish to harness LLMs to create personalised educational experiences.

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

• Understand the architecture and capabilities of LLMs.
• Identify opportunities for personalisation in educational content using LLMs.
• Design adaptive learning platforms that leverage LLMs for content personalisation.
• Implement LLM-driven strategies to enhance student engagement and learning outcomes.
• Evaluate the effectiveness of LLMs in educational settings and make data-driven decisions for

This instructor-led, live training in Christchurch (online or onsite) is aimed at intermediate-level ML practitioners and AI developers who wish to fine-tune and deploy open-weight models like LLaMA, Mistral, and Qwen for specific business or internal applications.

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

• Understand the ecosystem and differences between open-source LLMs.
• Prepare datasets and fine-tuning configurations for models like LLaMA, Mistral, and Qwen.
• Execute fine-tuning pipelines using Hugging Face Transformers and PEFT.
• Evaluate, save, and deploy fine-tuned models in secure environments.

This instructor-led, live training in Christchurch (available online or on-site) is designed for beginner to intermediate-level software developers and data scientists who wish to implement LLMs in speech recognition and synthesis systems.

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

• Understand the role of LLMs in speech technologies.
• Implement LLMs to achieve accurate speech recognition and natural-sounding speech synthesis.
• Integrate LLMs with speech recognition engines and speech synthesizers.
• Evaluate and enhance the performance of speech systems using LLMs.
• Stay informed about current trends and future directions in speech technologies.

This instructor-led, live training in Christchurch (online or on-site) is designed for beginner to intermediate-level customer support and IT professionals who wish to implement LLMs to build responsive and intelligent customer support chatbots.

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

• Grasp the fundamentals and architecture of Large Language Models (LLMs).
• Design and integrate LLMs into customer support systems.
• Improve the responsiveness and user experience of chatbots.
• Address ethical considerations and ensure compliance with industry standards.
• Deploy and maintain an LLM-based chatbot for real-world applications.

This instructor-led, live training in Christchurch (available online or on-site) is tailored for intermediate-level data scientists and AI engineers seeking to fine-tune large language models in a more cost-effective and efficient manner using methods such as LoRA, Adapter Tuning, and Prefix Tuning.

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

• Grasp the theoretical foundations of parameter-efficient fine-tuning approaches.
• Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
• Compare the performance and cost trade-offs between PEFT methods and full fine-tuning.
• Deploy and scale fine-tuned LLMs with significantly reduced computational and storage demands.

This instructor-led, live training in Christchurch (online or on-site) is aimed at intermediate-level to advanced-level machine learning engineers, AI developers, and data scientists who wish to learn how to use QLoRA to efficiently fine-tune large models for specific tasks and customisations.

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

• Understand the theory behind QLoRA and quantisation techniques for LLMs.
• Implement QLoRA in fine-tuning large language models for domain-specific applications.
• Optimise fine-tuning performance on limited computational resources using quantisation.
• Deploy and evaluate fine-tuned models in real-world applications efficiently.

This instructor-led, live training in Christchurch (delivered online or on-site) is designed for intermediate-level data and marketing professionals seeking to apply LLMs to analyse and interpret public sentiment from diverse text sources, including social media posts, product reviews, and customer feedback.

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

• Grasp the fundamental principles of sentiment analysis and its application using LLMs.
• Preprocess and prepare datasets for sentiment analysis.
• Train and fine-tune LLMs to accurately capture sentiment within text.
• Conduct real-time sentiment analysis on social media and other text-based sources.
• Integrate insights from sentiment analysis into business strategies and decision-making processes.

This instructor-led, live training in Christchurch (available online or on-site) is designed for intermediate-level software developers and technical writers seeking to harness LLMs to streamline their coding workflows and produce detailed, comprehensive documentation.

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

• Understand the role of LLMs in automating code generation and software documentation.
• Leverage LLMs to create accurate and efficient code snippets and documentation.
• Integrate LLMs into their software development lifecycle to enhance productivity.
• Maintain high-quality documentation standards using automated tools.
• Address ethical considerations and best practices for using AI in software development.

This instructor-led, live training in Christchurch (online or onsite) is designed for intermediate-level business professionals and data analysts who wish to harness the power of LLMs to extract valuable business insights.

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

• Understand the fundamentals and applications of LLMs within the context of business intelligence.
• Apply LLMs to analyse large datasets and extract meaningful insights.
• Integrate LLM-driven analytics into strategic business decision-making processes.
• Evaluate the ethical considerations and best practices for using LLMs in business.
• Anticipate future trends in AI and prepare for the evolving landscape of business intelligence.

This instructor-led, live training in Christchurch (online or on-site) is aimed at intermediate to advanced-level developers and data scientists who wish to master LlamaIndex for developing innovative LLM-powered applications.

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

• Set up and configure LlamaIndex for use with LLMs.
• Index and query custom datasets using LlamaIndex to enhance LLM functionality.
• Design and develop sophisticated applications that leverage LlamaIndex and LLMs.
• Understand and apply best practices for working with LLMs and LlamaIndex.
• Navigate the ethical considerations involved in deploying LLM-powered applications.

This instructor-led, live training in Christchurch (online or onsite) is aimed at intermediate-level AI researchers, machine learning professionals, and data scientists who wish to use LlamaIndex to enhance the capabilities of AI models, making them more accurate and reliable for various applications.

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

• Understand the principles and components of LlamaIndex.
• Ingest and structure data for use with LLMs.
• Implement context augmentation to improve AI model performance.
• Integrate LlamaIndex into existing AI systems and workflows.

This instructor-led, live training in Christchurch (online or on-site) is designed for intermediate-level professionals seeking to harness the power of prompt engineering and few-shot learning to enhance LLM performance in real-world scenarios.

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

• Grasp the core principles of prompt engineering and few-shot learning.
• Craft effective prompts for a variety of NLP tasks.
• Apply few-shot techniques to adapt LLMs using minimal data.
• Optimise LLM performance for practical, real-world applications.

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.
• Plenty of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

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

This instructor-led, live training (available online or on-site) is designed for advanced-level engineers, AI specialists, and localisation leads who wish to implement large language model (LLM) systems for automated translation, quality evaluation, and enterprise governance.

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

• Build enterprise-grade LLM localisation pipelines that integrate both open-source and proprietary models.
• Implement automated QA workflows and quality metrics to ensure translation consistency.
• Establish governance and approval frameworks for multilingual content production.
• Deploy scalable, auditable LLM-based localisation systems within secure environments.

AI for SQL involves applying artificial intelligence and large language models (LLMs) to automate, optimise, and enhance how SQL queries are generated, executed, and interpreted within enterprise data environments.

This instructor-led, live training (available online or on-site) is designed for intermediate-level data engineers and technical leads who wish to integrate AI capabilities into SQL workflows to enable natural language querying, intelligent optimisation, and automated data analysis.

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

• Integrate LLMs such as GPT, DeepSeek, LLaMA, Qwen, and Mistral into SQL environments.
• Build natural-language-to-SQL pipelines for conversational data access.
• Implement AI-driven query optimisation and error detection.
• Design secure, auditable AI-SQL workflows for enterprise use.

Course Format

• Interactive lectures and discussions.
• Abundant exercises and practice opportunities.
• Hands-on implementation in a live-lab environment.

Course Customisation Options

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

LangGraph is a framework for building 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 optimise 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 Customisation Options

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

Vertex AI offers robust tools for developing multimodal LLM workflows that seamlessly integrate text, audio, and image data into a unified pipeline. With support for extended context windows and configurable Gemini API parameters, it enables sophisticated applications in planning, reasoning, and cross-modal intelligence.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level practitioners who aim to design, build, and optimise multimodal AI workflows within Vertex AI.

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

• Leverage Gemini models for multimodal inputs and outputs.
• Implement long-context workflows to support complex reasoning tasks.
• Design pipelines that integrate analysis of text, audio, and images.
• Optimise Gemini API parameters for both performance and cost efficiency.

Course Format

• Interactive lectures and group discussions.
• Practical labs focused on multimodal workflows.
• Project-based exercises addressing real-world multimodal use cases.

Course Customisation Options

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

LangGraph enables stateful, multi-actor workflows powered by large language models (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 align seamlessly with clinical workflows.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level professionals who wish to design, implement, and manage LangGraph-based healthcare solutions while navigating regulatory, ethical, and operational challenges.

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

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

Course Format

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

Course Customisation Options

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and localisation engineers who wish to design scalable, automated translation pipelines using both proprietary and open-source LLMs.

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

• Design and deploy translation workflows using modern LLM frameworks and APIs.
• Integrate open-source and commercial models into scalable translation systems.
• Optimise translation quality through fine-tuning, prompt engineering, and automation.
• Implement cost-efficient and compliant translation infrastructure for enterprise environments.

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

This instructor-led, live training (available online or on-site) is designed for advanced-level AI platform engineers, AI-focused DevOps professionals, and ML architects who aim to optimise, debug, monitor, and operate production-grade LangGraph systems.

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

• Design and optimise complex LangGraph topologies for speed, cost-efficiency, and scalability.
• Engineer 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 lectures and discussions.
• Extensive exercises and hands-on practice.
• Real-world 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 (available online or on-site) is designed for intermediate-level developers seeking to learn how to apply generative AI with LLMs across various tasks and domains.

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

• Explain what generative AI is and how it works.
• Describe the transformer architecture that powers LLMs.
• Use empirical scaling laws to optimise LLMs for different tasks and constraints.
• Apply state-of-the-art tools and methods to train, fine-tune, and deploy LLMs.
• Discuss the opportunities and risks of generative AI for society and business.

LLMs and autonomous agent frameworks such as AutoGen and CrewAI are transforming how DevOps teams automate tasks like change tracking, test generation, and alert triage by emulating human-like collaboration and decision-making.

This instructor-led, live training (delivered online or on-site) is designed for advanced-level engineers who wish to design and implement DevOps automation workflows powered by large language models (LLMs) and multi-agent systems.

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

• Integrate LLM-based agents into CI/CD workflows for intelligent automation.
• Automate test generation, commit analysis, and change summaries using agents.
• Coordinate multiple agents for triaging alerts, generating responses, and delivering DevOps recommendations.
• Build secure and maintainable agent-powered workflows using open-source frameworks.

Course Format

• Interactive lecture and discussion.
• Abundant exercises and practical activities.
• 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.

Postgres is an advanced open-source relational database that serves as a robust foundation for AI-powered systems and data intelligence applications.

This instructor-led, live training (available online or on-site) is designed for intermediate-level database professionals and developers who aim to integrate, manage, and optimise AI capabilities directly within Postgres.

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

• Set up and configure Postgres extensions tailored for AI workloads.
• Implement embeddings and similarity search using pgvector.
• Integrate both open-source and proprietary LLMs with Postgres to deliver real-time insights.
• Optimise Postgres to efficiently handle AI-driven queries and workflows.

Course Format

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

Course Customisation Options

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

This instructor-led, live training in Christchurch (online or onsite) is aimed at intermediate-level to advanced-level AI developers, architects, and product managers who wish to identify and mitigate risks associated with LLM-powered applications, including prompt injection, data leakage, and unfiltered output, while incorporating security controls like input validation, human-in-the-loop oversight, and output guardrails.

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

• Understand the core vulnerabilities of LLM-based systems.
• Apply secure design principles to LLM app architecture.
• Use tools such as Guardrails AI and LangChain for validation, filtering, and safety.
• Integrate techniques like sandboxing, red teaming, and human-in-the-loop review into production-grade pipelines.

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

This instructor-led, live training (online or on-site) 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 Customisation Options

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

This instructor-led, live training in Christchurch (delivered online or onsite) is designed for intermediate to advanced-level professionals who wish to customise pre-trained models for particular tasks and datasets.

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

• Understand the principles of fine-tuning and its applications.
• Prepare datasets for fine-tuning pre-trained models.
• Fine-tune large language models (LLMs) for NLP tasks.
• Optimise model performance and address common challenges.

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

This instructor-led, live training (online or on-site) is aimed at 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 behaviour 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 Customisation Options

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

LLMs for Code Understanding, Refactoring, and Documentation is a technical course focused on applying large language models (LLMs) to enhance code quality, reduce technical debt, and automate documentation tasks across software teams.

This instructor-led, live training (delivered either online or on-site) is designed for intermediate to advanced-level software professionals who wish to leverage LLMs, such as GPT, to more effectively analyse, refactor, and document complex or legacy codebases.

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

• Use LLMs to explain code, dependencies, and logic in unfamiliar repositories.
• Identify and refactor anti-patterns while improving code readability.
• Automatically generate and maintain inline comments, README files, and API documentation.
• Integrate LLM-driven insights into existing CI/CD and review workflows.

Course Format

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

Course Customisation Options

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

This instructor-led, live training in Christchurch (available online or on-site) is designed for intermediate-level data scientists, AI developers, and AI enthusiasts who wish to leverage LLMs to carry out diverse NLP tasks and create innovative, varied content for multiple purposes.

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

• Set up a development environment equipped with LLMs and essential tools.
• Expertly execute NLU and NLI tasks using LLMs.
• Effectively extract, infer, and apply knowledge graphs.
• Generate and manage dialogues with LLMs for conversational applications.
• Evaluate the quality and diversity of content produced by LLMs and generative AI.
• Apply ethical principles to ensure fairness and responsible use of LLMs.

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.

Course Format

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

Course Customisation Options

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

This instructor-led, live training in Christchurch (available online or on-site) is designed for developers at the beginner to intermediate level who wish to leverage Large Language Models for various natural language tasks.

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

• Set up a development environment that includes a popular LLM.
• Create a basic LLM and fine-tune it on a custom dataset.
• Apply LLMs to different natural language tasks such as text summarisation, question answering, text generation, and more.
• Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.

This instructor-led, live training in Christchurch (online or on-site) is designed for intermediate-level engineers and architects who wish to leverage Tencent Hunyuan to deploy large and MoE models with reduced latency, enhanced throughput, and improved cost control.

By the end of this training, participants will be able to: explain Hunyuan production deployment patterns, optimise inference performance, implement batching and quantisation strategies, and plan scalable serving operations.

This instructor-led, live training in Christchurch (online or on-site) is designed for intermediate-level developers, technical product teams, and AI practitioners who wish to use Hunyuan models to create multimodal applications for image, 3D, and video generation and delivery.

By the end of this training, participants will be able to: build prompt-based workflows, generate and review multimodal assets, serve outputs through apps or APIs, and connect Hunyuan capabilities to enterprise product stacks.

This instructor-led, live training in Christchurch (online or on-site) is aimed at beginner-level, intermediate-level, or advanced-level AI professionals who wish to use MCP to connect AI assistants with external tools, data, and enterprise services.

By the end of this training, participants will be able to: explain MCP concepts, identify key architecture components, set up a basic integration, and apply security best practices.

This instructor-led, live training in Christchurch (online or on-site) is aimed at intermediate-level enterprise architects who wish to use the Model Context Protocol to design secure, scalable, and governable agent integration platforms for enterprise environments.

By the end of this training, participants will be able to: explain MCP architecture and enterprise patterns, design secure integration platforms, apply governance and access controls, and evaluate deployment and scaling options.

This instructor-led, live training in Christchurch (online or onsite) is aimed at intermediate-level developers, architects, and platform engineers who wish to use MCP to build reliable servers and clients for enterprise deployment and operations.

By the end of this training, participants will be able to: explain MCP architecture in practice, build production-ready integrations, deploy and observe MCP services, and apply versioning, resilience, and support patterns.

This instructor-led, live training in Christchurch (online or on-site) is aimed at intermediate-level IT leaders, compliance professionals, security teams, and enterprise architects who wish to use sovereign AI principles and governance practices to design AI environments that protect sensitive data, support localisation requirements, and reduce vendor lock-in.

By the end of this training, participants will be able to: explain sovereign AI concepts, evaluate hosting and governance options, define controls for prompts and logs, and create a practical adoption roadmap.