AI Agents Training in Paris

This instructor-led, live training in Paris (online or onsite) is aimed at advanced-level AI engineers, robotics developers, and automation specialists who wish to leverage DeepSeek for building intelligent AI agents and autonomous systems.

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

• Understand 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 increasingly embedded within decision-making structures across diverse sectors, including defense, healthcare, finance, and infrastructure. As these systems acquire greater independence and operational autonomy, there is a pressing demand for comprehensive ethical frameworks, governance mechanisms, and regulatory oversight to steer their design and implementation.

This instructor-led live training, available either online or onsite, is designed for advanced professionals seeking to understand the ethical, societal, and regulatory dimensions of deploying autonomous AI agents in practical environments.

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

• Examine the ethical risks and moral challenges associated with autonomous AI agents.
• Evaluate governance frameworks and regulatory models pertinent to high-stakes AI deployments.
• Assess mechanisms for accountability, explainability, and transparency within autonomous systems.
• Formulate strategies to align AI agent behavior with legal, ethical, and societal standards.

Course Format

• Interactive lectures and group discussions.
• Case studies and role-playing simulations.
• Practical analysis of governance models and ethical frameworks.

Customization Options

• For customized training arrangements for this course, please contact us to discuss your needs.

AI-driven automation merges the flexibility of no-code platforms with the intelligence of large language models and autonomous agents to build scalable, smart systems.

This instructor-led live training (available online or onsite) targets intermediate-level professionals aiming to design, construct, and optimize automation pipelines enriched with AI-driven decision-making, orchestration, and self-execution features.

Upon completing this training, participants will be able to:

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

Course Format

• Interactive lecture and discussion.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live lab environment.

Course Customization Options

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

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

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

• Grasp the security risks and ethical challenges involved in AI agent development.
• Implement design principles that prioritize security for AI models.
• Apply adversarial robustness techniques to protect AI agents from attacks.
• Ensure compliance with ethical AI guidelines and regulatory standards.

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.

This instructor-led, live training in Paris (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.
• Optimize multi-modal AI pipelines for efficiency and accuracy.
• Deploy multi-modal AI agents in real-world applications.

This instructor-led, live training in Paris (online or onsite) is designed for developers and designers at beginner to intermediate levels who want to understand and build AI-powered personal assistants for various applications.

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

• Grasp the core principles of AI-driven personal assistants.
• Learn the fundamentals of integrating language models with smart assistants.
• Develop and customize a personal assistant using AI frameworks and tools.
• Deploy personal assistants for practical applications across different industries.

This instructor-led, live training in Paris (online or onsite) is aimed at advanced-level AI engineers, enterprise software developers, and business leaders who wish to customize 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.
• Customize 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 Paris (online or onsite) is designed for advanced robotics engineers, AI researchers, and automation specialists who wish to develop AI-driven autonomous robotic systems for complex tasks and human-AI collaboration.

Upon completing this training, participants will be able to:

• Grasp the role of AI agents in robotic decision-making and automation.
• Implement AI-driven navigation and obstacle avoidance mechanisms.
• Develop robotic systems that support human-AI collaboration.
• Deploy AI-powered perception and control systems within robots.

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

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

• Comprehend the role of AI in financial automation and fraud detection.
• Construct AI models capable of detecting fraudulent transactions.
• Utilize machine learning for real-time risk assessment.
• Deploy AI-powered financial monitoring systems.

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

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

• Grasp the core principles of AI-powered customer support.
• Create and integrate AI chatbots to manage customer inquiries.
• Utilize NLP and machine learning to enrich chatbot interactions.
• Deploy AI agents in practical customer service environments.

This instructor-led, live training in Paris (online or onsite) is designed for healthcare professionals and AI developers at intermediate to advanced levels who wish to implement AI-driven healthcare solutions.

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

• Understand 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 ethical AI practices.

This instructor-led, live training in Paris (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 offers a robust suite of open-source and enterprise-grade AI models designed for language processing, multimodal applications, and agentic workflows.

This instructor-led live training, available online or onsite, is tailored for intermediate to advanced professionals aiming to construct, deploy, and manage AI agents utilizing Mistral’s Medium 3, Le Chat Enterprise, and Devstral models.

Upon completing this training, participants will be equipped to:

• Grasp the architecture and capabilities of Mistral Medium 3, Le Chat Enterprise, and Devstral.
• Design and implement AI agents using Mistral models for both enterprise and developer scenarios.
• Integrate coding systems, connectors, and enterprise data into agent workflows.
• Optimize the performance, cost-efficiency, and compliance of Mistral-powered agents.

Course Format

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

Customization Options

• To request 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.

Google Antigravity serves as an agentic development environment tailored for constructing autonomous agents that can plan, reason, code, and execute actions utilizing Gemini 3’s multimodal capabilities.

This instructor-led, live training—available online or onsite—is designed for advanced technical professionals eager to design, build, and deploy autonomous agents using Gemini 3 and the Antigravity environment.

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

• Construct autonomous workflows leveraging Gemini 3 for reasoning, planning, and execution.
• Develop agents within Antigravity capable of analyzing tasks, writing code, and interacting with external tools.
• Integrate Gemini-driven agents into enterprise systems and APIs.
• Optimize agent behavior, ensuring safety and reliability in complex operational environments.

Format of the Course also allows for the evaluation of participants.

• 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 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.

This instructor-led, live training in Paris (online or onsite) is designed for 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.
• Utilize tools such as Docker and Kubernetes to containerize and orchestrate AI agents.
• Monitor and optimize AI agents within production environments.
• Implement CI/CD workflows for AI agent deployments.
• Ensure compliance with security and data governance requirements.

This instructor-led, live training in Paris (online or onsite) is targeted 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 Paris (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 Paris (online or onsite) is designed for advanced AI professionals aiming 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 Paris (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 Paris (online or onsite) is aimed at intermediate-level business analysts, RPA developers, and AI professionals who wish to harness the power of AI agents for business process automation.

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

• Understand the role of AI agents in business process automation.
• Identify opportunities for automation in 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 optimize AI automation strategies for efficiency.

Vertex AI Agent Builder provides a no-code and low-code platform for constructing grounded agents that integrate generative AI models with Retrieval-Augmented Generation (RAG). This empowers teams to swiftly create agents that leverage enterprise data and search capabilities to deliver precise, context-sensitive responses.

This live, instructor-led training, available either online or on-site, is designed for intermediate practitioners looking to design, configure, and deploy intelligent agents using Vertex AI Agent Builder and RAG methodologies.

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

• Design grounded agent workflows utilizing Agent Builder.
• Construct RAG pipelines incorporating search and vector storage.
• Securely integrate enterprise data sources for retrieval purposes.
• Evaluate and refine agent performance through testing and metrics.

Course Format

• Interactive lectures and discussions.
• Practical labs featuring Vertex AI Agent Builder and RAG components.
• Project-based exercises to build and refine agents.

Customization Options

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

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

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

• Grasp the role of AI agents in modern gaming.
• Create decision-making systems using decision trees and finite state machines.
• Implement pathfinding algorithms, such as A*, for in-game navigation.
• Apply reinforcement learning techniques to develop adaptive AI behaviors.
• Optimize AI performance for real-time gaming environments.

Large language models (LLMs) and autonomous agent frameworks such as AutoGen and CrewAI are transforming how DevOps teams automate critical tasks—including change tracking, test generation, and alert triage—by emulating human-like collaboration and decision-making processes.

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

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

• Integrate LLM-based agents into CI/CD workflows to enable intelligent automation.
• Automate test generation, commit analysis, and change summaries using agent-driven approaches.
• Coordinate multiple agents to triage alerts, generate appropriate responses, and provide actionable DevOps recommendations.
• Develop secure and maintainable agent-powered workflows utilizing open-source frameworks.

Course Format

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

Customization Options

• To request a tailored version of this course, please contact us to arrange your specific needs.

This instructor-led, live training in Paris (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 Paris (online or onsite) is aimed at intermediate-level professionals who wish to delve deeper into the design and development of autonomous agents for practical applications.

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

• Understand 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 for automation and decision-making.
• Address ethical considerations and challenges in deploying autonomous agents.

Devstral is an open-source framework purpose-built for creating and operating coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.

This instructor-led live training, available online or onsite, targets intermediate to advanced ML engineers, developer-tooling teams, and SREs who aim to design, implement, and optimize coding agents using Devstral.

Upon completion 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.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and hands-on practice.
• Live-lab implementation exercises.

Customization Options

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

This instructor-led, live training in Paris (online or onsite) is designed for beginner-level professionals who wish to understand how AI agents work and build their own interactive chatbot systems.

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

• Understand the basics of AI agents and their applications.
• Explore the principles of natural language processing (NLP).
• Design a conversational flow for a chatbot.
• Develop a functional chatbot using Python and related tools.
• Deploy the chatbot to interact with real users.

This instructor-led, live training in Paris (online or onsite) is aimed at beginner-level professionals who wish to understand and create simple AI agents for real-world applications.

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

• Understand the fundamental concepts of AI agents.
• Identify different types of AI agents and their applications.
• Design and implement basic AI agents for practical tasks.
• Explore tools and frameworks for building AI agents.

This instructor-led, live training in Paris (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.

This advanced, hands-on seminar is tailored for software engineers, architects, technical leads, engineering managers, and delivery teams seeking to leverage Artificial Intelligence to accelerate the entire software delivery lifecycle, spanning from requirements analysis to the production of ready-to-deploy code.

This instructor-led, live training in Paris (online or on-site) is designed for developers and technical professionals at beginner, intermediate, and advanced levels 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 live, instructor-led training in Paris (online or onsite) is designed for software developers and DevOps teams who wish to use OpenAI Codex CLI to automate coding tasks, review code, and execute multi-step workflows from the terminal.

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

This instructor-led, live training [in 6loc7] (online or onsite) targets developers aiming 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 Paris (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 Paris (online or onsite) targets intermediate-level solution architects, AI engineers, developers, and technical product teams looking to use Tencent ADP to build enterprise AI agents equipped with RAG, workflow automation, and operational guardrails.

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 guardrails.

This instructor-led, live training in Paris (online or onsite) is designed for beginner, intermediate, and advanced developers and technical practitioners who wish to utilize Google Cloud to build AI agents capable of automating tasks, using tools, and interacting with business data.

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

This instructor-led live training in Paris (online or onsite) targets developers and DevOps professionals aiming to leverage Hermes Agent to automate development workflows, manage infrastructure, and establish persistent AI processes.

Upon completion, participants will be able to install and configure Hermes Agent, interact with it across multiple platforms, use over 40 built-in tools, and deploy on various backends.

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

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

This instructor-led, live training in Paris (online or onsite) is intended for developers who wish 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 Paris (online or onsite) is aimed at developers and technical teams who wish to use Ollama and open-source 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-source models locally, create simple agentic and retrieval-based workflows, and apply security and governance controls for regulated environments.

This instructor-led, live training in Paris (online or onsite) targets backend developers who aim to build MCP-compatible tool servers and integrate them with agent clients.

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

This instructor-led, live training in Paris (online or onsite) targets beginner, intermediate, and advanced-level AI professionals who wish to use MCP to link 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 architectural components, set up a basic integration, and apply security best practices.

This instructor-led, live training in Paris (online or on-site) is designed for beginner to intermediate-level developers and technical teams wishing to utilize OpenAI APIs to build AI agents capable of reasoning, tool usage, and multi-step task completion.

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

This instructor-led, live training in Paris (online or onsite) targets intermediate-level to advanced 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 Paris (online or onsite) targets 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, conducted Paris (online or on-site), is designed for developers who wish to utilize 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, effectively set up and use the tool, apply it to practical coding tasks, and adopt secure team workflows.

This instructor-led, live training in Paris (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.