Agentic AI Training in Tours

This live training on Tours examines the impact of agentic AI on organizational workflows, talent strategies, and job design. Suited for intermediate professionals, it addresses autonomous decision-making, enterprise readiness, and governance frameworks to guarantee responsible and compliant AI adoption.

This instructor-led bootcamp in Tours provides a practical pathway for building autonomous AI agents in Python. Participants will complete five progressive projects that cover design patterns, API orchestration, and multi-agent workflows, bridging the gap between theory and real-world deployment.

This practical course in Tours walks you through the process of deploying agentic AI on resource-limited devices. You will learn to construct, optimize, and manage lightweight agents for local reasoning using Python, TensorFlow Lite, and PyTorch Mobile, thereby boosting speed, privacy, and reliability.

This live, instructor-led training in Tours provides an introduction to agentic AI, addressing prompt engineering, design patterns, and ethical usage. Learners will gain the skills to construct simple agent workflows using Python, integrate external tools, and apply safety measures to ensure the effectiveness, security, and scalability of autonomous systems.

This live, instructor-led training in Tours supports intermediate professionals in designing and scaling agentic AI for business automation. Participants will learn to map workflows, integrate tools, and construct practical use cases in customer service, supply chain, and marketing to ensure tangible, measurable impact.

This live training in Tours empowers advanced professionals to architect and deploy multi-agent systems using Python. The curriculum covers agent coordination, reinforcement learning, and distributed computing with frameworks such as Mesa and Ray, culminating in a practical capstone project.

This instructor-led training in Tours focuses on reinforcement learning and strategic decision-making for agentic AI. Participants will implement DQN, PPO, and A3C algorithms using Python, model environments with OpenAI Gym, and apply these techniques to robotics and planning systems to achieve effective real-world adaptive behavior.

This live training in Tours empowers advanced professionals to scale and operationalize agentic AI systems in production. It addresses MLOps, observability, and cost control, enabling the creation of resilient, observable, and cost-optimized pipelines for large-scale deployments.

This instructor-led training in Tours delves into governance, identity management, and red-teaming for agentic AI. It empowers advanced practitioners to architect secure deployments, enforce least-privilege access, and conduct adversarial testing to address real-world production threats.

This instructor-led, live training in Tours emphasizes practical Python implementation for autonomous AI agents. It explores modern SDKs like LangChain and AutoGen, empowering engineers to build, connect, and orchestrate complex agent workflows with assurance.

This live, instructor-led training in Tours focuses on practical Python techniques for creating autonomous agents. Key topics include agent loops, tool integration, memory handling, orchestration, and safety protocols. Designed for ML engineers, it emphasizes the deployment of robust, production-ready agent systems.

This instructor-led, live training in Tours (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.

This instructor-led, live training in Tours (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.

This instructor-led, live training in Tours (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.

This instructor-led, live training in Tours (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.

This instructor-led, live training in Tours (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.

This instructor-led, live training in Tours (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.

This five-day course in Tours empowers finance professionals with advanced analytics, AI-assisted Python, and agentic AI capabilities. Participants will learn to build intelligent dashboards, streamline GL operations, and design autonomous workflows to support financial analysis, reporting, and strategic decision-making.

This one-day course equips software engineers, technical leads, and development teams with a practical framework for leveraging AI coding agents effectively in real-world projects. Moving beyond simple prompting techniques, the curriculum explores the entire agent ecosystem, covering context engineering, reusable workflows, MCP (Model Context Protocol) integrations, feedback loops, security measures, and organizational adoption strategies.

AI agents are transitioning from experimental prototypes to robust production systems capable of autonomous operation across text, image, speech, and tool-driven workflows. This shift demands heightened engineering rigor, resilience against adversarial threats, and strict regulatory accountability. This instructor-led training guides advanced practitioners through the complete agent lifecycle, covering the architecture of single and multi-agent systems, integration of multi-modal perception, and orchestration of coordinated behaviors using modern frameworks. Through progressively complex Python-based labs, participants construct a production-grade multi-agent system and stress-test it with adversarial techniques and the Adversarial Robustness Toolbox. The course concludes with alignment to NIST AI RMF, ISO/IEC 42001, the EU AI Act, and GDPR, alongside secure deployment, monitoring, and incident response protocols, ensuring participants can deliver agents that are capable, defensible, and compliant.

This instructor-led live training in Tours (available online or onsite) is designed for beginner to intermediate developers and cloud practitioners who intend to use Alibaba Cloud to build AI agents capable of automating tasks, answering queries, and integrating with business systems.

By the end of this training, participants will be able to understand the architecture of AI agents on Alibaba Cloud, construct a basic agent workflow, link an agent to enterprise knowledge sources and tools, and deploy and monitor the agent within a cloud environment.

This instructor-led, live training in Tours is targeted at intermediate-level developers who intend to design, develop, and test AI agents using the Claude API and the Agent SDK.

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

• Utilize the Messages API with system prompts, structured outputs, and streaming
• Define tools and establish a dependable tool-use loop
• Link agents to external systems through MCP servers
• Develop and operate agents using the Claude Agent SDK, including permissions and subagents
• Minimize cost and latency via prompt caching and optimized context handling
• Test, log, and monitor agent behavior using a small evaluation set

Rather than processing single prompts, Claude Cowork assumes end-to-end responsibilities for research, document creation, and file management. This training guides you through crafting effective briefs, monitoring execution plans, and validating outputs. Learners will delegate three practical assignments and configure automated recurring tasks.

Delivered by an expert trainer in a live format in Tours, this session is designed for knowledge workers, assistants, and team leads who prefer delegating complete workflows to Claude over iterative step-by-step conversations.

Upon completion, participants will be able to:

• Distinguish between interactive chat and delegated work within Cowork
• Draft assignments that clearly define objectives, inputs, constraints, and success criteria
• Generate documents, spreadsheets, and presentations from existing folder content
• Delegate research processes from initial inquiry to final report delivery
• Leverage plugins, skills, and connectors within the Cowork ecosystem
• Establish approval checkpoints, backup protocols, and secure folder access controls

Training Structure

• Duration: 1 day (7 hours)
• Interactive workshop featuring live instruction, collaborative discussions, and hands-on exercises tailored to participants' specific use cases
• Day 1 Outcome: Each participant will have delegated three real-world tasks to Cowork, verified the outputs, and implemented a scheduled automation.

Customization Options

• Please reach out to discuss requirements for a tailored training experience.

Enable teams to resolve knowledge-based questions and support document workflows with precision and control. This two-day curriculum introduces Agent Builder on the first day and delves into Copilot Studio, including approval workflows and testing protocols, on the second. Attendees will conclude the session with a tested knowledge agent and a foundational draft for a Studio agent.

Conducted as live, instructor-led training in Tours, this course is designed for key users, AI champions, and department leads aiming to build custom Copilot agents for knowledge queries and document processes.

Upon completion, participants will be equipped to:

• Determine when Copilot Chat is sufficient versus when a specialized agent is necessary
• Construct a knowledge agent in Agent Builder, specifying the audience, knowledge sources, and limitations
• Comprehend the architecture of agents in Copilot Studio and develop a first prototype
• Dissect document workflows into reviewable steps involving human approval
• Validate agents using test cases and acceptance criteria
• Organize roles, permissions, licenses, and operational aspects

Course Format

• Duration: 2 days (7 hours each)
• Interactive sessions with a trainer, including discussions and hands-on exercises focused on participants' own use cases
• Day 1 Outcome: Each participant will have a tested knowledge agent and a tool map for their specific work cases.
• Day 2 Outcome: Each participant will have a draft Studio agent with approval features, two tested process cases, and a roadmap for their use cases.

Customization Options

• To request a tailored training experience for this course, please contact us for arrangements.

An AI assistant grounded in corporate documentation can address inquiries regarding policies, manuals, and workflows while explicitly citing the source material. This course guides participants through the essential steps of document preparation, platform selection, code-free agent construction, and performance evaluation using a structured question catalog. Additionally, participants will draft a comprehensive maintenance plan.

This live, instructor-led training in Tours is designed for teams, knowledge owners, and key users aiming to derive accurate responses from their proprietary documents, policies, and manuals.

Upon completing this training, participants will be equipped to:

• Grasp the mechanics of Retrieval-Augmented Generation (RAG) in simple terms and identify the inherent limitations of AI responses
• Optimize document preparation to ensure answer accuracy
• Select the most suitable platform for deploying a knowledge agent
• Construct and distribute a knowledge agent without requiring coding skills
• Validate responses using a question catalog and source references
• Establish protocols for maintenance, role allocation, and content currency in operational environments

Course Structure

• Duration: 1 day (7 hours)
• Interactive sessions featuring expert guidance, collaborative discussions, and hands-on exercises tailored to participants' specific use cases
• Day 1 Deliverable: Each participant will possess a shared knowledge agent based on their own documents, along with a measured accuracy rate and a documented maintenance plan.

Customization Availability

• For customized training tailored to this course, please reach out to arrange details.

Langdock serves as a unified platform that aggregates various AI models, assistants, corporate knowledge, and workflow automation for enterprise use. This course delves into everyday applications such as chat management, assistant creation and sharing, knowledge source integration, and the setup of approval-based workflows. It also covers critical governance aspects, including data rules, role assignments, and rollout strategies.

This live, instructor-led training in Tours is designed for: Key stakeholders and departments in companies adopting or using Langdock as a central AI solution.

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

• Confidently operate Langdock across chat, model management, assistant creation, knowledge bases, and workflows
• Select the optimal model for each specific task
• Create and share team assistants infused with custom instructions and company knowledge
• Establish a knowledge base by connecting SharePoint, OneDrive, and other relevant sources
• Configure basic workflows that incorporate human approval mechanisms
• Formulate organizational rules for data security, user roles, and approval processes

Course Format

• Duration: Two days (seven hours per day), or available as four half-day online modules
• Interactive sessions with expert guidance, open discussions, and practical exercises focused on participants' use cases
• Day 1 Goal: Participants will possess a template, a knowledge folder, and a shared assistant tailored to their area of responsibility.
• Day 2 Goal: Participants will have a functioning workflow with approval features, a linked knowledge source, and a 30-60 day implementation plan.

Customization Options

• To tailor this course to your specific needs, please reach out to our team for arrangements.

This live, instructor-led training in Tours is designed for intermediate professionals aiming to automate business operations and create their initial AI agent using Make.

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

• Design no-code workflows in Make employing triggers and webhooks.
• Link AI agents to their data within a specific flow.
• Automate a genuine process from start to finish, incorporating error handling and monitoring capabilities.

A personal AI agent can streamline tasks such as email sorting, appointment scheduling, briefing preparation, and running daily routines like a morning overview. This one-day course guides you through the setup process, emphasizing personal context, connector integration, and clear protocols for approvals and data protection. Participants will conclude the session with a functional agent and two active routines.

This live, instructor-led training in Tours is designed for professionals, assistants, project managers, and self-employed individuals seeking to implement a personal AI agent to support their workflow.

Upon completion, participants will be equipped to:

• Distinguish between tasks a personal AI agent can handle and those requiring human intervention
• Construct a personalized context using profiles, specific instructions, and notes
• Manage email and calendar interactions with AI assistance while maintaining full control
• Enhance appointment and conversation readiness through automated briefings
• Establish recurring routines, including morning overviews and weekly reviews
• Implement specific approval workflows, data protection measures, and operational limits for the agent

Course Format

• Duration: 1 day (7 hours)
• Interactive learning with a trainer, including discussions and hands-on exercises tailored to participants' specific use cases
• Outcome: By the end of Day 1, each participant will have a configured personal agent with a profile, connected mailbox and calendar, and two active routines.

Customization Options

• To arrange a customized training session for this course, please get in touch with us.

This instructor-led, live training in Tours is aimed at: Managers, assistants and knowledge workers.

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

• Organise email and calendar with AI support
• Prepare meetings and research faster
• Set up a personal assistant with your own preferences
• Protect personal and company data