Agentic AI training courses, delivered either online or onsite with an instructor, use interactive, hands-on practice to show how autonomous decision-making systems can automate tasks, enable data-driven decisions, and optimize business processes.
Agentic AI training is offered as "online live training" or "onsite live training". Online live training (also referred to as "remote live training") is conducted via an interactive remote desktop. Onsite live training can take place locally at your premises in Nantes or at NobleProg corporate training centers in Nantes.
NobleProg -- Your Local Training Provider
Nantes, Zenith
NobleProg Nantes, 4 rue Edith Piaf, Saint-Herblain, france, 44821
In the Parc d'Ar Mor zone, near the Zénith.
Car : from the ring road, Porte de Chézine Exit> Boulevard du Zenith > Esplanade Georges Brassens (restaurants) > Rue Edith Piaf on the right. From the N444 road (Nantes > Lorient), Exit #1 > boulevard Marcel Paul > Rue Edith Piaf at the right.
Parking Zénith P1 (free). Once parked, you can recognize the building: it's one of the tree bulding with zinc frontage.
Bicycle: free indoor parking
Public transport :
Tramway R1, Schoelcher station + 10 mn by foot through commercial center Atlantis
Tramway R1, François Mitterrand stop + bus 50, stop at Saulzaie station or bus 71, stop at the Zénith station
Tramway R3, Marcel Paul station + bus 50, Saulzaie station
Chronobus C6, Hermeland station+ bus 71, Zénith station
Bus : lignes 50 (Saulzaie station) or 71 (Zénith station)
Generative AI and Agentic AI represent two powerful paradigms driving the next wave of automation and intelligence. One focuses on content generation, while the other enables goal-driven, autonomous behavior.
This instructor-led live training (available online or onsite) is designed for intermediate-level AI and technical professionals who want 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 also allows for the evaluation of participants.
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 represents a new generation of systems capable of making independent decisions, executing tasks, and orchestrating workflows autonomously.
This instructor-led training, available either online or onsite, is designed for intermediate-level professionals seeking to understand how agentic AI will transform organizational workflows, talent strategies, and job design.
After completing this course, participants will be able to:
Assess the strengths and limitations of agentic AI within enterprise environments.
Identify opportunities for task automation, augmentation, and process redesign.
Evaluate workforce implications and formulate responsible adoption strategies.
Develop governance frameworks to ensure safe, transparent, and compliant AI deployment.
Course Format
Interactive lectures and discussions.
Practical exercises and scenario-based analyses.
Hands-on exploration of agentic workflows in a guided environment.
Course Customization Options
To request customized training for this course, please contact us to make arrangements.
The Practical Agentic AI Bootcamp is a rigorous, project-centric program designed to equip participants with hands-on experience in creating, 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 (available online or onsite) targets intermediate-level professionals eager to transition quickly from theory to implementation by developing functional prototypes of agentic AI applications.
By the end of this training, participants will be able to:
Comprehend agentic AI architectures and core 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 enhanced performance and reliability.
Apply best practices for monitoring, versioning, and scaling agent systems.
Course Format
Interactive lectures combined with 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.
The "Edge & Lightweight Agents" course offers practical guidance on deploying agentic AI workloads on devices with limited resources. Participants will learn to develop, optimize, and manage lightweight agents that perform local reasoning and inference, thereby enhancing speed, privacy, and reliability in distributed systems. Key focus areas include performance tuning, low-latency design, and hardware-software integration.
This instructor-led, live training is available online or onsite, targeting intermediate professionals who aim to implement and optimize on-device agentic systems using Python and edge AI frameworks.
Upon completion of this training, participants will be capable of:
Grasping the architecture and challenges of running agentic AI on edge devices.
Designing lightweight agent loops tailored for constrained environments.
Executing local inference using TensorFlow Lite, PyTorch Mobile, and ONNX.
Integrating agents with sensors, actuators, and IoT platforms.
Optimizing performance, energy consumption, and latency for real-time operations.
Course Format
Interactive lectures accompanied by practical demonstrations.
Hands-on development within local or emulated environments.
Project-based learning with guided implementation exercises.
Customization Options
For customized training on this course, please contact us to arrange your session.
Agentic AI describes systems capable of acting autonomously to achieve specific goals, by integrating reasoning capabilities, memory, and tool usage. This course offers a structured introduction to the core concepts of agentic AI, with a focus on prompt engineering, architectural design patterns, and best practices for responsible deployment. Participants will acquire the foundational knowledge needed to effectively and safely build, guide, and deploy AI agents.
Delivered as instructor-led live training (available online or onsite), this program is designed for beginner to intermediate professionals who want to learn how to design, prompt, and manage responsible agentic systems using practical frameworks and real-world examples.
Upon completion of this training, participants will be able to:
Explain the fundamental principles and lifecycle of agentic AI systems.
Apply prompt engineering techniques to facilitate efficient task completion.
Design straightforward agent workflows utilizing tool access and decision logic.
Implement safety measures, governance protocols, and responsible-use guidelines within AI agents.
Construct a prototype agent using open-source frameworks and Python.
Format of the Course also allows for the evaluation of participants.
Interactive lectures combined with guided demonstrations.
Hands-on exercises and coding practice.
Collaborative discussions and case-based activities.
Course Customization Options
To request a customized training session for this course, please contact us to arrange your requirements.
Agentic AI for Business Automation is a practical course designed to equip participants with the skills to design, integrate, and scale AI-driven agents for real-world business processes. The curriculum emphasizes identifying automation opportunities, integrating essential tools, and constructing practical use cases across customer service, supply chain, and marketing workflows.
This instructor-led, live training (available online or onsite) is tailored for intermediate-level professionals looking to implement AI-powered automation using no-code, low-code, and Python-based approaches.
By the conclusion 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 also allows for the evaluation of participants.
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 delves into the design, coordination, and implementation of multi-agent systems (MAS) using Python. Participants will learn how to construct agents that communicate, collaborate, and adapt to achieve shared objectives in complex, dynamic environments.
This instructor-led, live training (available online or onsite) is targeted 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:
Grasp 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 also allows for the evaluation of participants.
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 delves into the principles and practical implementation of reinforcement learning (RL) and sequential decision-making within the context of agentic AI systems. Participants will gain the skills to design, train, and assess agents capable of dynamic interaction with their environments, ultimately achieving long-term objectives through continuous learning and adaptation.
Delivered as instructor-led live training, available either online or onsite, this program is tailored for advanced engineers and researchers looking to incorporate reinforcement learning and planning algorithms into agentic systems for applications in automation, robotics, and adaptive reasoning.
Upon completion of this training, participants will be able to:
Grasp the mathematical foundations underpinning reinforcement learning and decision-making processes.
Code essential RL algorithms, including DQN, PPO, and A3C, utilizing Python and PyTorch.
Construct environments using OpenAI Gym and create custom simulation scenarios.
Train, evaluate, and debug agents designed for both continuous and discrete control tasks.
Apply reinforcement learning methodologies to real-world agentic AI use cases, particularly in robotics and planning.
Effectively manage the balance between exploration, exploitation, and safety constraints during real-world deployment.
Format of the Course also allows for the evaluation of participants.
Instructor-led lectures coupled with live coding demonstrations.
Practical exercises leveraging open-source frameworks and simulation environments.
An applied project focused on integrating decision-making capabilities into an agentic AI system.
Course Customization Options
For personalized training requirements regarding this course, please contact us to arrange a tailored solution.
This course is dedicated to scaling, operationalizing, and managing agentic AI systems within production environments, with a strong emphasis on reliability, observability, and cost efficiency.
Offered as an instructor-led, live training session (available online or onsite), it targets advanced professionals aiming to construct resilient, observable, and cost-optimized pipelines for large-scale agentic systems.
Upon completion of this training, participants will be equipped to:
Design scalable architectures tailored for agentic AI workloads.
Implement observability and monitoring frameworks specifically adapted for agent behavior and interactions.
Apply performance tuning and resource optimization techniques for long-running agent processes.
Control costs and mitigate "agent sprawl" through effective policy, orchestration, and automation.
Integrate MLOps best practices for the continuous deployment, versioning, and rollback of agentic services.
Format of the Course also allows for the evaluation of participants.
Hands-on, engineering-focused sessions supported by live infrastructure examples.
Interactive discussions on architectural trade-offs and observability challenges.
Capstone exercise involving the deployment and monitoring of a cost-controlled, production-grade agentic system.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
WrenAI empowers organizations to transition from static dashboards to conversational analytics and embedded generative BI. Achieving this shift demands strategic adoption planning, asset migration, and robust change management practices.
This instructor-led live training (available online or onsite) is designed for intermediate-level BI and data platform professionals seeking to modernize their legacy BI systems using WrenAI.
Upon completing this training, participants will be able to:
Evaluate existing legacy BI environments to identify modernization opportunities.
Plan and execute the migration from static dashboards to WrenAI.
Implement conversational analytics and embedded GenBI capabilities.
Lead organizational change management initiatives for BI modernization.
Course Format
Interactive lectures and discussions.
Hands-on exercises focused on migration and adoption planning.
Practical labs covering conversational analytics and embedded GenBI.
Course Customization Options
To request customized training for this course, please contact us to make arrangements.
This course provides comprehensive coverage of governance, identity management, and adversarial testing for agentic AI systems, with a focus on enterprise-safe deployment patterns and practical red-teaming techniques.
Delivered as instructor-led live training (available online or onsite), this program targets advanced-level practitioners seeking to design, secure, and evaluate agent-based AI systems within production environments.
Upon completion of this training, participants will be able to:
Define governance models and policies to ensure safe agentic AI deployments.
Design non-human identity and authentication flows for agents, enforcing least-privilege access.
Implement access controls, audit trails, and observability mechanisms tailored to autonomous agents.
Plan and execute red-team exercises to identify misuses, escalation paths, and data exfiltration risks.
Mitigate common threats to agentic systems through policy, engineering controls, and continuous monitoring.
Format of the Course also allows for the evaluation of participants.
Interactive lectures and threat-modeling workshops.
Hands-on labs covering identity provisioning, policy enforcement, and adversary simulation.
Red-team/blue-team exercises and an end-of-course assessment.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
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 build, connect, and manage agent workflows.
Delivered as an instructor-led live training (available online or onsite), this program is designed for intermediate-level backend, platform, and ML engineers who aim to implement and orchestrate autonomous agents using Python tooling and APIs.
Upon completion of this training, participants will be equipped to:
Set up and configure Python-based environments for agentic systems.
Leverage popular agent SDKs, including LangChain and AutoGen, to develop functional agents.
Integrate tools and APIs to expand agent capabilities.
Orchestrate multi-agent workflows and communication patterns.
Apply best practices for debugging, testing, and maintaining agentic codebases.
Course Format
Interactive lectures and discussions.
Hands-on programming exercises and live demonstrations.
Practical projects focused on building end-to-end agent workflows.
Course Customization Options
To request a customized training session for this course, please contact us to arrange.
WrenAI empowers finance teams 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 also allows for the evaluation of participants.
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 delivers practical engineering methodologies for designing, building, testing, and deploying agentic (autonomous) systems using Python. It explores the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.
This instructor-led, live training (available online or onsite) is designed for intermediate to advanced ML engineers, AI developers, and software engineers seeking to build robust, production-ready autonomous agents using Python.
By the conclusion of this training, participants will be able to:
Design and implement the agent loop and decision-making workflows.
Integrate external tools and APIs to expand agent capabilities.
Implement short-term and long-term memory architectures for agents.
Coordinate multi-step orchestrations and agent composability.
Apply safety, access control, and observability best practices for deployed agents.
Course Format
Interactive 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 facilitates the conversion of natural language into SQL queries and delivers AI-driven analytics, streamlining data access to make it faster and more intuitive. For enterprise-level deployment, robust quality assurance and observability practices are critical to guarantee accuracy, reliability, and regulatory compliance.
This instructor-led, live training (available online or on-site) targets advanced data and analytics professionals seeking to evaluate query precision, implement prompt tuning strategies, and deploy observability protocols for monitoring WrenAI in production environments.
Upon completion of this training, participants will be equipped to:
Assess the accuracy and reliability of natural language to SQL conversions.
Utilize prompt tuning methods to enhance system performance.
Monitor for drift and analyze query behavior over time.
Instrument WrenAI with logging and observability frameworks.
Course Format
Interactive lectures and group discussions.
Practical exercises focused on evaluation and tuning techniques.
Hands-on labs covering observability and monitoring integrations.
Customization Options
For customized training arrangements for this course, please contact us.
Agentic AI refers to a methodology where artificial intelligence systems are capable of planning, reasoning, and utilizing tools to achieve specific objectives within established boundaries.
This instructor-led live training, available online or in-person, is designed for intermediate-level healthcare and data professionals seeking to design, assess, and manage agentic AI solutions for both clinical and operational scenarios.
Upon completion of this course, participants will be equipped to:
Articulate the core principles and limitations of agentic AI within healthcare environments.
Construct secure agent workflows that incorporate planning, memory retention, and tool integration.
Develop retrieval-augmented agents that leverage clinical documentation and knowledge repositories.
Assess, oversee, and govern agent conduct using safety guardrails and human-in-the-loop mechanisms.
Course Format
Interactive lectures coupled with guided discussions.
Directed laboratory exercises and code walkthroughs conducted in a sandbox setting.
Scenario-based activities focusing on safety, assessment, and governance.
Customization Options
To arrange a tailored training program for this course, please reach out to us.
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 also allows for the evaluation of participants.
Interactive lecture and discussion.
Hands-on labs with governance and security configurations.
This instructor-led, live training in Nantes (online or onsite) targets intermediate-level AI developers and automation specialists seeking to integrate agentic functionalities into AI-powered applications.
By the conclusion of this training, participants will be able to:
Comprehend the principles of agentic AI and autonomous decision-making.
Develop goal-driven AI agents utilizing self-optimization techniques.
Integrate multi-agent collaboration for complex problem-solving scenarios.
Enhance AI-human interaction through adaptive user experiences.
Deploy agentic AI models in real-world applications.
The WrenAI Spreadsheets and Metrics Library facilitate rapid reporting by leveraging AI-driven spreadsheet workflows and a repository of pre-built, cross-platform business metrics.
This instructor-led live training (available online or onsite) is designed for operations professionals at beginner to intermediate levels who aim to accelerate their reporting and analytical processes using WrenAI Spreadsheets and the Metrics Library.
Upon completion of this training, participants will be able to:
Develop AI-enhanced spreadsheets for data analysis and reporting.
Utilize the WrenAI Metrics Library to establish standardized Key Performance Indicators (KPIs).
Link spreadsheets to various data sources to ensure real-time updates.
Design automated workflows to streamline operational reporting.
Course Format
Interactive lectures and discussions.
Practical, hands-on experience building spreadsheets with WrenAI.
Practical exercises focused on metrics and KPI reporting.
Course Customization Options
For requests regarding customized training for this course, please contact us to arrange details.
This instructor-led, live training in Nantes (online or onsite) is designed for advanced professionals seeking to develop and optimize multi-agent systems using Agentic AI frameworks.
Upon completing this training, participants will be capable of:
Grasping the core principles of Agentic AI within multi-agent environments.
Building AI-driven agents that interact autonomously.
Implementing reinforcement learning to enable adaptive AI behaviors.
Optimizing both collaboration and competition among multiple agents.
Applying Agentic AI solutions in robotics, gaming, and enterprise automation.
The WrenAI API serves as a robust interface for transforming natural language into SQL queries, developing custom applications, and embedding charts within internal platforms.
This instructor-led, live training (available online or on-site) is designed for intermediate-level engineers seeking to leverage the WrenAI API for practical use cases, including SQL generation, data visualization, and application integration.
Upon completion of this training, participants will be able to:
Authenticate and establish connections between applications and the WrenAI API.
Generate SQL queries from natural language inputs.
Create and embed charts using specific API endpoints.
Integrate WrenAI into backend systems and internal tooling.
Course Format
Interactive lectures and discussions.
Hands-on exercises involving API calls and integrations.
Practical projects that connect applications, charts, and data pipelines.
Customization Options
To request a customized training session for this course, please contact us to arrange details.
This instructor-led, live training in Nantes (online or onsite) is designed for advanced professionals seeking to utilize Agentic AI for enterprise-scale automation and strategic AI integration.
Upon completing this training, participants will be capable of:
Grasping the role of Agentic AI within enterprise applications.
Integrating autonomous AI agents with enterprise systems.
Optimizing AI-driven workflows for improved scalability and efficiency.
Ensuring compliance, security, and governance in AI automation.
Developing AI-driven business strategies to support digital transformation.
WrenAI Cloud is a contemporary platform designed to connect data sources, model data, and create interactive dashboards.
This instructor-led, live training (available online or onsite) is intended for beginner to intermediate-level data professionals who want 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 also allows for the evaluation of participants.
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 Nantes (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:
Grasp the foundational principles of autonomous decision-making within AI.
Design and deploy AI agents that function with minimal human oversight.
Seamlessly integrate Agentic AI into existing automation workflows and business infrastructure.
Enhance the efficiency and scalability of AI-driven decision processes.
Uphold compliance, security standards, and ethical guidelines regarding AI autonomy.
WrenAI is an open-source generative business intelligence tool that facilitates the conversion of natural language into SQL and supports semantic data modeling.
This instructor-led training session, available online or on-site, is designed for advanced-level data engineers, analytics engineers, and ML engineers who aim to construct robust semantic layers, refine prompts, and guarantee reliable SQL generation.
Upon completion of this training, participants will be able to:
Deploy semantic models to establish consistent metric definitions across teams.
Enhance text-to-SQL performance to ensure accuracy and scalability.
Configure and enforce guardrails to prevent invalid or high-risk queries.
Integrate WrenAI OSS into existing data pipelines and analytics workflows.
Course Format
Interactive lectures and discussions.
Numerous exercises and practice sessions.
Hands-on implementation within a live laboratory environment.
Course Customization Options
To request customized training for this course, please contact us to arrange details.
This instructor-led, live training in Nantes (online or onsite) targets intermediate-level AI engineers, ML researchers, and developers aiming to build and deploy Agentic AI systems in practical applications.
By the end of this training, participants will be able to:
Grasp the fundamental principles of Agentic AI systems.
Develop AI agents capable of autonomous reasoning and action.
Integrate Agentic AI with APIs and third-party services.
Optimize interactions among multiple agents for complex tasks.
Address ethical, security, and scalability challenges inherent in Agentic AI.
WrenAI empowers SaaS providers to embed generative business intelligence (GenBI) directly within their customer-facing applications. This course equips SaaS teams with the necessary skills to integrate Wren AI via its Embedded API, configure white-label analytics, and manage multi-tenant deployments effectively.
This instructor-led, live training (available online or onsite) is designed for intermediate to advanced SaaS product leaders, data engineers, and full-stack developers seeking to deploy WrenAI as an embedded analytics solution within SaaS environments.
Upon completion of this training, participants will be able to:
Integrate WrenAI using the Embedded API for customer-facing applications.
Implement white-label conversational BI features with custom branding and styling.
Design secure and scalable multi-tenant architectures.
Monitor usage metrics, optimize performance, and ensure compliance within SaaS environments.
Course Format
Interactive lectures and discussions.
Hands-on labs utilizing the WrenAI Embedded API.
Workshop: Design and deploy a white-label analytics feature tailored for a specific SaaS use case.
Course Customization Options
To request a customized training session for this course, please contact us to arrange.
This instructor-led, live training in Nantes (online or in-person) targets beginner-level professionals seeking to understand the fundamental concepts of Agentic AI, its capabilities, and its potential impact across industries.
Upon completing this training, participants will be able to:
Comprehend the core principles of Agentic AI.
Distinguish between traditional AI and autonomous AI agents.
Examine real-world applications of Agentic AI across various sectors.
Evaluate the advantages and challenges associated with deploying autonomous AI systems.
Analyze the ethical and security implications 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 also allows for the evaluation of participants.
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 transitioning from research prototypes to autonomous production systems capable of operating across text, image, speech, and tool-driven workflows. This shift necessitates higher standards for engineering rigor, resilience against adversarial threats, and regulatory accountability. This instructor-led training guides advanced practitioners through the entire agent lifecycle, from designing single and multi-agent architectures to integrating multi-modal perception and coordinating agent behaviors via modern frameworks. Through progressive Python-based labs, participants will construct a production-ready multi-agent system, which they will then rigorously stress-test using adversarial techniques and the Adversarial Robustness Toolbox. The course concludes with a focus on aligning with NIST AI RMF, ISO/IEC 42001, the EU AI Act, and GDPR, alongside secure deployment, continuous monitoring, and incident response protocols, ensuring participants can deploy agents that are capable, defensible, and compliant.
This instructor-led, live training in Nantes (online or onsite) targets beginner to intermediate-level 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 the architecture of AI agents on Alibaba Cloud, build a simple agent workflow, connect an agent to enterprise knowledge and tools, and deploy and monitor an agent in a cloud environment.
Read more...
Last Updated:
Testimonials (4)
The trainer is patient and very helpful. He knows the topic well.
CLIFFORD TABARES - Universal Leaf Philippines, Inc.
Course - Agentic AI for Business Automation: Use Cases & Integration
Good mixvof knowledge and practice
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Agentic AI for Enterprise Applications
The mix of theory and practice and of high level and low level perspectives
Ion Mironescu - Facultatea S.A.I.A.P.M.
Course - Autonomous Decision-Making with Agentic AI
Online Agentic AI training in Nantes, Agentic AI training courses in Nantes, Weekend Agentic AI courses in Nantes, Evening Agentic AI training in Nantes, Agentic AI instructor-led in Nantes, Agentic AI trainer in Nantes, Online Agentic AI training in Nantes, Evening Agentic AI courses in Nantes, Agentic AI instructor in Nantes, Weekend Agentic AI training in Nantes, Agentic AI boot camp in Nantes, Agentic AI classes in Nantes, Agentic AI coaching in Nantes, Agentic AI instructor-led in Nantes, Agentic AI on-site in Nantes, Agentic AI one on one training in Nantes, Agentic AI private courses in Nantes
