Agentic AI Training in Ontario

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 behavior.

This instructor-led, live training (online or onsite) 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 Customization Options

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

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to understand how agentic AI will reshape organizational workflows, talent strategies, and job design.

Upon completion of 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.

Format of the Course

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

Course Customization Options

• To request a customized training 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.
• Optimize 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 Customization Options

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

Edge & Lightweight Agents is a practical course focused on deploying agentic AI workloads on resource-constrained devices. Participants learn to build, optimize, and manage lightweight agents capable of local reasoning and inference, improving speed, privacy, and reliability in distributed environments. The course emphasizes 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 optimize 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.
• Optimize 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 Customization Options

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

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.

Format of the Course

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

Course Customization Options

• To request a customized training 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.

Format of the Course

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

Course Customization Options

• To request a customized training 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 onsite) 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 behaviors.
• Design hybrid workflows combining humans and intelligent agents.

Format of the Course

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

Course Customization Options

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

This course explores the principles and implementation of reinforcement learning (RL) and sequential decision-making as they apply to agentic AI systems. Participants will learn how to design, train, and evaluate agents that interact dynamically with their environments to achieve long-term goals through learning and adaptation.

This instructor-led, live training (online or onsite) is aimed at advanced-level engineers and researchers who wish to integrate reinforcement learning and planning algorithms into agentic systems for automation, robotics, and adaptive reasoning.

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

• Understand the mathematical foundations of reinforcement learning and decision-making.
• Implement key RL algorithms such as DQN, PPO, and A3C using Python and PyTorch.
• Model environments using OpenAI Gym and design custom simulation scenarios.
• Train, evaluate, and debug agents for continuous and discrete control tasks.
• Apply reinforcement learning techniques to agentic AI use cases in robotics and planning.
• Balance exploration, exploitation, and safety constraints in real-world deployment.

Format of the Course

• Instructor-led lectures and live coding demonstrations.
• Hands-on exercises using open-source frameworks and simulation environments.
• Applied project integrating decision-making into an agentic AI system.

Course Customization Options

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

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

This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to build resilient, observable, and cost-optimized 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 behavior and interactions.
• Apply performance tuning and resource optimization 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 Customization Options

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

WrenAI enables organizations 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 modernize legacy BI systems with WrenAI.

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

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

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 Customization Options

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

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

This instructor-led, live training (online or onsite) is aimed at 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 discover 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-modeling workshops.
• Hands-on labs: identity provisioning, policy enforcement, and adversary simulation.
• Red-team/blue-team exercises and end-of-course assessment.

Course Customization Options

• To request a customized training 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 (online or onsite) is aimed at 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 Customization Options

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

WrenAI provides finance teams with the ability to model KPIs, integrate standardized metrics, and design dashboards that align with regulatory requirements and audit standards.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level finance professionals who wish to use WrenAI for building compliant financial data models and dashboards that support decision-making and risk management.

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

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

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises with financial data models.
• Practical labs on dashboard design and compliance reporting.

Course Customization Options

• To request a customized training for this course, 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-level 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.

Format of the Course

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

Course Customization Options

• To request a customized training 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 behavior 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 Customization Options

• To request a customized 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 behavior 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 Customization Options

• To request a customized 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 onsite) 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 organizations.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with governance and security configurations.
• Practical exercises simulating enterprise rollout scenarios.

Course Customization Options

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

This instructor-led, live training in Ontario (online or onsite) is aimed at intermediate-level AI developers and automation specialists who wish to integrate agentic capabilities into AI-powered applications.

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

• Understand the principles of agentic AI and autonomous decision-making.
• Implement goal-driven AI agents with self-optimization techniques.
• Integrate multi-agent collaboration for complex problem-solving.
• Enhance AI-human interaction through adaptive user experiences.
• Deploy agentic AI models in real-world applications.

WrenAI Spreadsheets and Metrics Library enable fast reporting through AI-powered spreadsheet workflows and a library of pre-built, cross-platform business metrics.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level operations professionals who wish to accelerate reporting and analysis using WrenAI Spreadsheets and the Metrics Library.

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

• Build AI-powered spreadsheets for data analysis and reporting.
• Leverage the WrenAI Metrics Library for standardized KPIs.
• Connect spreadsheets to multiple data sources for live updates.
• Create automated workflows to streamline operational reporting.

Format of the Course

• Interactive lecture and discussion.
• Hands-on spreadsheet building with WrenAI.
• Practical exercises with metrics and KPI reporting.

Course Customization Options

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

This instructor-led, live training in Ontario (online or onsite) is aimed at advanced-level professionals who wish to develop and optimize multi-agent systems using Agentic AI frameworks.

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

• Understand the principles of Agentic AI in multi-agent environments.
• Develop AI-driven agents that interact autonomously.
• Implement reinforcement learning for adaptive AI behavior.
• Optimize multi-agent collaboration and competition.
• Apply Agentic AI in robotics, gaming, and enterprise automation.

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level engineers who wish to use the WrenAI API for practical applications, including SQL generation, visualization, and app 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.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises with API calls and integrations.
• Practical projects connecting apps, charts, and data pipelines.

Course Customization Options

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

This instructor-led, live training in Ontario (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for enterprise-scale automation and strategic AI adoption.

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

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

WrenAI Cloud is a modern platform for connecting data sources, modeling 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 visualize 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 modeling.
• Practical exercises in dashboard building and visualization.

Course Customization Options

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

This instructor-led, live training in Ontario (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 modeling.

This instructor-led, live training (online or onsite) 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.
• Optimize 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.

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 Ontario (online or onsite) is aimed at 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.
• Optimize multi-agent interactions for complex tasks.
• Address ethical, security, and scalability challenges in Agentic AI.

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

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level SaaS product leaders, data engineers, and full-stack developers who wish to deploy WrenAI as an embedded analytics solution in 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 branding and customization.
• Design secure and scalable multi-tenant deployments.
• Monitor usage, optimize performance, and ensure compliance in SaaS environments.

Format of the Course

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

Course Customization Options

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

This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level professionals who wish to understand the fundamental principles of Agentic AI, its capabilities, and its potential impact on industries.

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

• Understand the core principles of Agentic AI.
• Differentiate between traditional AI and autonomous AI agents.
• Explore real-world applications of Agentic AI in various industries.
• Assess the benefits and challenges of deploying autonomous AI systems.
• Analyze the ethical and security considerations of 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 standardized 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 Customization Options

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

AI agents are moving from research demos to production systems that act autonomously across text, image, speech, and tool-driven workflows, raising the bar for engineering rigor, adversarial robustness, and regulatory accountability. This instructor-led training takes advanced practitioners through the full agent lifecycle, from architecting single and multi-agent systems to integrating multi-modal perception and orchestrating coordinated agent behavior through modern frameworks. Hands-on labs in Python build progressively toward a production-grade multi-agent system, which participants then stress-test using adversarial techniques and the Adversarial Robustness Toolbox. The course closes with NIST AI RMF, ISO/IEC 42001, EU AI Act, and GDPR alignment, secure deployment, monitoring, and incident response, so participants leave able to ship agents that are capable, defensible, and compliant.

This instructor-led, live training in Ontario (online or onsite) is aimed at beginner-level / intermediate-level developers and cloud practitioners who wish to use Alibaba Cloud to build AI agents that can automate tasks, answer questions, and connect 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.