AI Agents Training in Brisbane

This instructor-led, live training in Brisbane (online or onsite) targets advanced-level AI engineers, robotics developers, and automation specialists aiming to leverage DeepSeek for constructing intelligent AI agents and autonomous systems.

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

• Comprehend the architecture and capabilities of DeepSeek AI models.
• Integrate DeepSeek into AI agents for decision-making and automation.
• Apply reinforcement learning techniques for training autonomous systems.
• Deploy AI-driven autonomous agents in real-world environments.

Autonomous AI agents are being rapidly integrated into decision-making processes across sectors such as defence, healthcare, finance, and infrastructure. As these systems gain greater independence and autonomy, there is an urgent need for robust ethical frameworks, governance mechanisms, and regulatory oversight to guide their design and deployment.

This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to explore the ethical, societal, and regulatory implications of deploying autonomous AI agents in real-world environments.

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

• Analyse the ethical risks and moral dilemmas posed by autonomous AI agents.
• Evaluate governance frameworks and regulatory models relevant to high-stakes AI deployment.
• Assess accountability, explainability, and transparency mechanisms in autonomous systems.
• Develop strategies for aligning AI agent behaviour with legal, ethical, and societal values.

Format of the Course

• Interactive lecture and discussion.
• Case studies and role-playing simulations.
• Hands-on analysis of governance models and ethical frameworks.

Course Customisation Options

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

AI-driven automation merges the adaptability of no-code platforms with the cognitive capabilities of large language models and autonomous agents to develop scalable, intelligent systems.

This instructor-led, live training (available online or onsite) targets intermediate-level professionals aiming to design, construct, and optimise automation pipelines bolstered by AI-driven decision-making, orchestration, and self-executing functions.

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

• Design no-code automation workflows augmented by AI interpretation and response mechanisms.
• Utilise prompt chaining, webhook triggers, and APIs to construct scalable logical flows.
• Develop intelligent applications that seamlessly connect services and autonomously interpret data.
• Understand, design, and deploy AI agents capable of goal-oriented action planning and execution.

Course Format

• Interactive lectures and discussions.
• Ample exercises and practical activities.
• Practical implementation within a live-lab environment.

Customisation Options

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

This instructor-led, live training in Brisbane (online or onsite) is designed for intermediate-level AI developers, security specialists, and compliance officers looking to design and implement secure AI agents while addressing ethical concerns and robustness.

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

• Understand the security risks and ethical challenges in AI agent development.
• Implement security-first design principles for AI models.
• Apply adversarial robustness techniques to prevent attacks on AI agents.
• Ensure compliance with ethical AI guidelines and regulatory standards.

Edge & Lightweight Agents is a practical course focused on deploying agentic AI workloads on resource-constrained devices. Participants learn to build, optimise, and manage lightweight agents capable of local reasoning and inference, improving speed, privacy, and reliability in distributed environments. The course emphasises performance tuning, low-latency design, and hardware–software integration.

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

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

• Understand the architecture and challenges of 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 use, and latency for real-time operation.

Format of the Course

• Interactive lecture and practical demonstrations.
• Hands-on development in local or emulated environments.
• Project-based learning and guided implementation exercises.

Course Customisation Options

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

This instructor-led, live training in Brisbane (online or onsite) is aimed at intermediate-level to advanced-level AI developers, researchers, and multimedia engineers who wish to build AI agents capable of understanding and generating multi-modal content.

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

• Develop AI agents that process and integrate text, image, and speech data.
• Implement multi-modal models such as GPT-4 Vision and Whisper ASR.
• Optimise multi-modal AI pipelines for efficiency and accuracy.
• Deploy multi-modal AI agents in real-world applications.

This instructor-led, live training in Brisbane (online or onsite) is aimed at beginner-level to intermediate-level developers and designers who wish to understand and build AI-powered personal assistants for various use cases.

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

• Understand the core principles of AI-powered personal assistants.
• Learn the fundamentals of integrating language models with smart assistants.
• Build and customize a personal assistant using AI frameworks and tools.
• Deploy personal assistants for real-world applications in different industries.

This instructor-led, live training in Brisbane (online or onsite) is aimed at advanced-level AI engineers, enterprise software developers, and business leaders who wish to customise and deploy LLM-based AI agents for enterprise applications.

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

• Understand the architecture and capabilities of open-source LLMs.
• Customise and fine-tune LLMs for enterprise use cases.
• Deploy AI agents using LangChain and Hugging Face.
• Integrate LLM-powered agents into business workflows.

This instructor-led, live training in Brisbane (online or onsite) is aimed at advanced-level robotics engineers, AI researchers, and automation specialists who wish to develop AI-driven autonomous robotic systems for complex tasks and human-AI collaboration.

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

• Understand the role of AI agents in robotic decision-making and automation.
• Implement AI-driven navigation and obstacle avoidance.
• Develop human-AI collaborative robotic systems.
• Deploy AI-powered perception and control systems in robots.

This programme investigates the design, coordination, and implementation of multi-agent systems (MAS) using Python. Participants will gain insights into constructing agents that communicate, collaborate, and adapt to achieve shared objectives within complex and dynamic environments.

This instructor-led, live training (available online or onsite) is targeted at advanced-level professionals looking to design and implement multi-agent systems for intelligent automation, simulation, and decision-making applications.

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

• Comprehend the architecture and principles underlying multi-agent systems.
• Develop agents capable of communication, coordination, and negotiation.
• Implement distributed environments for agent interactions.
• Apply reinforcement learning and planning techniques within multi-agent contexts.
• Simulate both cooperative and competitive agent behaviours.
• Design hybrid workflows that integrate humans and intelligent agents.

Course Format

• Instructor-led lectures and live demonstrations.
• Practical exercises utilising open-source agent frameworks.
• A collaborative group project simulating a multi-agent scenario.

Course Customisation Options

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

This instructor-led, live training in Brisbane (online or onsite) is designed for intermediate-level financial professionals, risk analysts, and AI engineers who wish to develop and deploy AI-driven solutions for financial automation and fraud detection.

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

• Grasp the role of AI in financial automation and fraud detection.
• Construct AI models to detect fraudulent transactions.
• Utilise machine learning for real-time risk assessment.
• Deploy AI-powered financial monitoring systems.

This instructor-led, live training in Brisbane (online or onsite) is aimed at beginner-level to intermediate-level customer service professionals, chatbot developers, and automation teams who wish to implement AI-driven solutions for customer support and service automation.

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

• Understand the fundamentals of AI-powered customer support.
• Develop and integrate AI chatbots for handling customer queries.
• Leverage NLP and machine learning to enhance chatbot interactions.
• Deploy AI agents in real-world customer service applications.

This instructor-led, live training in Brisbane (online or onsite) is designed for intermediate to advanced-level healthcare professionals and AI developers seeking to implement AI-driven healthcare solutions.

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

• Grasp the role of AI agents in healthcare and diagnostics.
• Develop AI models for medical image analysis and predictive diagnostics.
• Integrate AI with electronic health records (EHR) and clinical workflows.
• Ensure compliance with healthcare regulations and adhere to ethical AI practices.

This instructor-led, live training in Brisbane (online or onsite) is aimed at beginner-level to intermediate-level AI developers and UI/UX designers who wish to learn how to build, optimize, and deploy AI-powered virtual assistants.

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

• Design effective conversational AI workflows and UI/UX interfaces.
• Implement AI-driven natural language processing (NLP) models.
• Integrate AI assistants with APIs and third-party platforms.
• Deploy and maintain AI assistants for real-world applications.

Mistral AI provides a robust suite of open-source and enterprise-ready AI models designed for language, multimodal, and agentic applications.

This instructor-led live training, available online or on-site, targets intermediate to advanced professionals keen on building, deploying, and managing AI agents using Mistral's Medium 3, Le Chat Enterprise, and Devstral models.

Upon completion, participants will be equipped to:

• Grasp the architecture and capabilities of Mistral Medium 3, Le Chat Enterprise, and Devstral.
• Design and implement AI agents tailored for enterprise and developer use cases using Mistral models.
• Integrate coding systems, connectors, and enterprise data into agent workflows.
• Optimise performance, cost, and compliance for agents powered by Mistral.

Course Format

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

Customisation Options

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

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation using contemporary SDKs and frameworks, such as LangChain and AutoGen, to construct, link, and manage agent workflows.

This instructor-led, live training (available online or onsite) 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.
• Utilise 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 Customization Options

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

Google Antigravity is an agentic development environment designed to build autonomous agents capable of planning, reasoning, coding, and acting through Gemini 3’s multimodal capabilities.

This instructor-led, live training (online or onsite) is aimed at advanced-level technical professionals who wish to design, build, and deploy autonomous agents using Gemini 3 and the Antigravity environment.

Upon finishing this training, participants will be prepared to:

• Build autonomous workflows that use Gemini 3 for reasoning, planning, and execution.
• Develop agents in Antigravity that can analyze tasks, write code, and interact with tools.
• Integrate Gemini-driven agents with enterprise systems and APIs.
• Optimize agent behavior, safety, and reliability in complex environments.

Format of the Course

• Expert demonstrations combined with interactive discussions.
• Hands-on experimentation with autonomous agent development.
• Practical implementation using Antigravity, Gemini 3, and supporting cloud tools.

Course Customization Options

• If your team requires domain-specific agent behaviors or custom integrations, please contact us to tailor the program.

This course imparts practical engineering strategies for designing, constructing, testing, and deploying agentic (autonomous) systems using Python. Key topics include the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production-ready considerations.

Delivered as instructor-led, live training (available online or onsite), this program is tailored for intermediate to advanced-level ML engineers, AI developers, and software engineers looking to create robust, production-ready autonomous agents using Python.

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on labs for building agents using Python and popular SDKs.
• Project-based exercises that result in deployable prototypes.

Course Customisation Options

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

This instructor-led, live training in Brisbane (online or onsite) is aimed at advanced-level professionals who wish to master the techniques for deploying and managing AI agents in production environments.

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

• Design and implement scalable AI deployment pipelines.
• Use tools like Docker and Kubernetes to containerise and orchestrate AI agents.
• Monitor and optimise AI agents in production environments.
• Implement CI/CD workflows for AI agent deployments.
• Ensure compliance with security and data governance requirements.

This instructor-led, live training in Brisbane (online or onsite) is aimed at advanced-level AI professionals who wish to master reinforcement learning techniques and implement them for training AI agents in solving complex problems.

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

• Understand the core principles of reinforcement learning and Markov Decision Processes (MDPs).
• Design and implement RL algorithms such as Q-Learning, SARSA, and Deep Q-Networks (DQN).
• Utilize frameworks like OpenAI Gym and RL libraries for practical applications.
• Train AI agents to solve real-world, multi-step decision-making problems.
• Address challenges such as exploration-exploitation trade-offs and convergence in RL training.

This instructor-led, live training in Brisbane (online or onsite) is designed for intermediate-level AI developers and automation specialists looking to integrate agentic capabilities into AI-powered applications.

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

• Grasp the principles of agentic AI and autonomous decision-making.
• Develop goal-driven AI agents utilising self-optimisation techniques.
• Implement multi-agent collaboration for complex problem-solving.
• Improve AI-human interaction through adaptive user experiences.
• Deploy agentic AI models in real-world applications.

This instructor-led, live training in Brisbane (online or onsite) is aimed at advanced-level AI professionals who wish to master the skills to design, build, and deploy MAS that solve complex, real-world problems.

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

• Understand the principles of multi-agent system architectures.
• Implement strategies for communication, coordination, and decision-making in MAS.
• Apply game theory to model agent interactions and resolve conflicts.
• Leverage frameworks like JADE to create scalable MAS solutions.
• Address challenges like scalability, trust, and emergent behavior in MAS.

This instructor-led, live training in Brisbane (online or onsite) is designed for advanced-level professionals aiming to develop and optimise multi-agent systems using Agentic AI frameworks.

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

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

This instructor-led, live training in Brisbane (online or onsite) is designed for intermediate-level business analysts, RPA developers, and AI professionals keen on leveraging the power of AI agents for business process automation.

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

• Comprehend the role of AI agents in business process automation.
• Identify automation opportunities within key business domains.
• Develop AI-driven solutions for customer support, finance, and supply chain workflows.
• Integrate AI agents with existing RPA and business systems.
• Evaluate and optimise AI automation strategies for efficiency.

Vertex AI Agent Builder provides a no-code/low-code platform for developing grounded agents that merge generative models with Retrieval-Augmented Generation (RAG). This enables teams to quickly construct agents that leverage enterprise data and search capabilities to deliver accurate, context-aware responses.

This instructor-led, live training session (available online or onsite) is designed for intermediate-level practitioners seeking to design, configure, and deploy intelligent agents using Vertex AI Agent Builder and RAG architectures.

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

• Design grounded agent workflows using Agent Builder.
• Implement RAG pipelines utilizing search and vector stores.
• Securely integrate enterprise data sources for retrieval.
• Evaluate and refine agent behaviour through testing and metrics.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focusing on Vertex AI Agent Builder and RAG components.
• Project-based exercises to construct and refine agents.

Course Customization Options

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

This instructor-led, live training in Brisbane (online or onsite) is designed for intermediate-level game developers and AI enthusiasts who wish to effectively integrate AI agents into gaming applications.

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

• Grasp the significance of AI agents in contemporary gaming.
• Construct decision-making systems using decision trees and finite state machines.
• Deploy pathfinding algorithms, such as A*, for in-game navigation.
• Utilise reinforcement learning techniques to develop adaptive AI behaviours.
• Enhance AI performance for real-time gaming environments.

Large language models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming the way DevOps teams automate processes like change tracking, test generation, and alert triage by mimicking human-like collaboration and decision-making.

This instructor-led live training (delivered online or onsite) is tailored for advanced-level engineers looking to design and implement DevOps automation workflows driven by LLMs and multi-agent systems.

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

• Integrate LLM-powered agents into CI/CD workflows for intelligent automation.
• Automate test generation, commit analysis, and change summaries using agents.
• Orchestrate multiple agents to triage alerts, generate responses, and provide DevOps recommendations.
• Construct secure and maintainable agent-driven workflows using open-source frameworks.

Course Format

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

Course Customization Options

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

This instructor-led, live training in Brisbane (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.

This instructor-led, live training in Brisbane (online or onsite) is tailored for intermediate-level professionals looking to deepen their expertise in designing and developing autonomous agents for practical use.

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

• Grasp the foundational concepts of autonomous agents.
• Explore real-world applications of autonomous AI agents.
• Design, train, and implement agents using reinforcement learning.
• Integrate agents into existing systems to enhance automation and decision-making.
• Navigate ethical considerations and challenges associated with deploying autonomous agents.

Devstral is an open-source framework designed for building and running coding agents that can interact with codebases, developer tools, and APIs to enhance engineering productivity.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level ML engineers, developer-tooling teams, and SREs who wish to design, implement, and optimize coding agents using Devstral.

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

• Set up and configure Devstral for coding agent development.
• Design agentic workflows for codebase exploration and modification.
• Integrate coding agents with developer tools and APIs.
• Implement best practices for secure and efficient agent deployment.

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.

This instructor-led, live training in Brisbane (online or on-site) is designed for beginner-level professionals keen to understand how AI agents function and to build their own interactive chatbot systems.

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

• Grasping the fundamentals of AI agents and their practical applications.
• Investigating the principles of natural language processing (NLP).
• Crafting a conversational flow for a chatbot.
• Developing a functional chatbot using Python and associated tools.
• Deploying the chatbot to engage with real users.

This instructor-led, live training in Brisbane (online or onsite) is designed for beginner-level professionals keen to grasp and develop simple AI agents for practical, real-world scenarios.

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

• Grasp the fundamental concepts of AI agents.
• Recognise various types of AI agents and their respective applications.
• Design and implement basic AI agents to address practical tasks.
• Explore the tools and frameworks available for constructing AI agents.

This instructor-led, live training in Brisbane (online or onsite) targets beginner to intermediate developers and cloud practitioners who wish to use Alibaba Cloud to build AI agents capable of automating tasks, answering questions, and connecting 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, deploy and monitor an agent in a cloud environment.

This advanced, hands-on seminar is tailored for software engineers, architects, technical leads, engineering managers, and delivery teams keen to understand how Artificial Intelligence can expedite the entire software delivery lifecycle, spanning from requirements analysis through to production-ready code.

This instructor-led, live training in Brisbane (online or onsite) is aimed at beginner-level / intermediate-level / advanced-level developers and technical professionals who wish to use Microsoft Azure to build, test, and deploy AI agents for business applications.

By the end of this training, participants will be able to: understand AI agent architecture on Azure, create and configure a working agent, connect agents to business knowledge sources, evaluate and prepare agents for deployment.

This instructor-led live training in Brisbane (online or on-site) is aimed at software developers and DevOps teams who wish to use OpenAI Codex CLI to automate coding tasks, review code, and run multi-step workflows from the terminal.

By the end of this training, participants will be able to install and configure Codex CLI, execute tasks via natural language prompts, manage approval modes, and integrate with Git and CI pipelines.

This instructor-led, live training in Brisbane (online or onsite) is aimed at developers who wish to use GitHub Copilot Agent Mode to autonomously build features, run tests, and manage larger coding tasks.

By the end of this training, participants will be able to activate Agent Mode, plan and iterate within the agent loop, execute terminal commands, and implement enterprise governance.

This instructor-led, live training in Brisbane (online or onsite) is aimed at developers and leads who wish to use Cursor to build features faster, refactor across files, and manage team-wide AI workflows.

By the end of this training, participants will be able to navigate using Composer and agent mode, target code with context-aware chat, deploy team workspaces, and integrate Cursor with version control.

This instructor-led, live training in Brisbane (online or onsite) is aimed at intermediate-level solution architects, AI engineers, developers, and technical product teams who wish to use Tencent ADP to build enterprise AI agents with RAG, workflow automation, and operational safeguards.

By the end of this training, participants will be able to: design ADP-based agents, create knowledge pipelines, orchestrate workflows and multi-agent patterns, and apply production safeguards.

This instructor-led, live training in Brisbane (online or onsite) is aimed at beginner-level, intermediate-level, and advanced-level developers and technical practitioners who wish to use Google Cloud to build AI agents capable of automating tasks, utilising tools, and working with business data.

By the end of this training, participants will be able to explain AI agent concepts, build agents with Vertex AI, connect agents to external tools and data, and deploy agents for business use cases.

This instructor-led live training in Brisbane (online or onsite) is aimed at developers and DevOps professionals who wish to use Hermes Agent to automate development tasks, manage infrastructure, and build persistent AI workflows.

By the end of this training, participants will be able to install and configure Hermes Agent, interact with it across multiple platforms, use 40+ built-in tools, and deploy on various backends.

This instructor-led live training in Brisbane (online or onsite) is designed for business users, operations teams, and technical professionals wishing to use Hermes Agent to automate work, create reusable AI-driven processes, and boost team productivity.

By the end of this training, participants will be able to explain Hermes Agent basics, set up and use core features, build practical workflows, and apply sound operational practices.

This instructor-led, live training in Brisbane (online or onsite) is tailored for developers wishing to use Hermes Agent to design and run secure local AI workflows for code assistance.

By the end of this training, participants will be able to: explain Hermes Agent concepts, set up secure local agent environments, build practical coding workflows, and apply safety and governance controls.

This instructor-led live training in Brisbane (online or onsite) is aimed at developers and technical teams who wish to use Ollama and open models to build and run private agentic AI solutions on internal infrastructure.

By the end of this training, participants will be able to install and configure Ollama, evaluate and run open models locally, create simple agentic and retrieval-based workflows, and apply security and governance controls for regulated environments.

This instructor-led, live training in Brisbane (online or onsite) is aimed at backend developers who wish to build MCP-compatible tool servers and integrate them with agent clients.

By the end of this training, participants will be able to implement MCP servers, connect them to Claude Code and OpenClaude, switch transports, and maintain an internal tool registry.

This instructor-led, live training in Brisbane (online or onsite) is aimed at beginner, intermediate, or advanced 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 good practices.

This instructor-led, live training in Brisbane (online or onsite) is designed for beginner to intermediate developers and technical teams who wish to use OpenAI APIs to build AI agents capable of reasoning, utilising tools, and completing multi-step tasks.

By the end of this training, participants will be able to: design agent workflows, connect tools and external data, manage context and responses, and test agents for business use.

This instructor-led, live training in Brisbane (online or onsite) is aimed at intermediate-level / advanced-level developers and technical professionals who wish to use OpenClaw to build and run practical AI agents that automate work through chat and tool integrations.

By the end of this training, participants will be able to: install and configure OpenClaw, connect an LLM provider, use and adapt skills for automation, and apply basic security and operational guardrails.

This instructor-led, live training in Brisbane (online or onsite) is aimed at senior developers who wish to use Pi to build lightweight, customizable terminal agent workflows.

By the end of this training, participants will be able to install Pi, extend it with TypeScript skills, adapt workflows to team standards, and share extensions via npm.

This instructor-led, live training in Brisbane (online or onsite) is aimed at developers who wish to use Pi Coding Agent to generate code, review changes, and streamline terminal-based development workflows.

By the end of this training, participants will be able to: explain Pi Coding Agent concepts, set up and use the tool effectively, apply it to practical coding tasks, and adopt safe team workflows.

This instructor-led, live training in Brisbane (online or onsite) is aimed at developers who wish to use Windsurf to build features conversationally, execute terminal workflows inside the IDE, and refactor across the codebase.

By the end of this training, participants will be able to use Cascade for navigation, execute terminal commands inside the editor, leverage predictive edits, and customize Windsurf for proprietary stacks.