Whether conducted online or onsite, instructor-led live training courses on AI Agents illustrate, through interactive practical exercises, how to leverage AI agents to automate tasks, make smart decisions, and engage with users across various applications.
AI Agents training is offered in two formats: "online live training" and "onsite live training." Online live training (also referred to as "remote live training") is delivered via an interactive remote desktop. Onsite live training can be provided locally at your premises in Transylvania or at NobleProg’s corporate training centers in Transylvania.
NobleProg -- Your Local Training Provider
Brasov, Calea Bucuresti Street
NobleProg Brasov, 13 Calea Bucuresti Street Sacele, Brasov, romania, 505600
The hotel is situated at the city entrance, being the best conference and training location in Brasov. Three conference rooms can accommodate up to 170 guests and can be modified for the company needs. These training rooms are equipped with the all necessities of a good conference or training.
Salile de training sunt situate central în Sibiu, pe principalul bulevard. Clădirea hotelului care le gazduieste este de factură clasicistă si reprezinta un punct de referinta arhitecturala a orasului.
Turnul Sfatului, Galeria de Arta Contemporana, sau parcurile Corneliu Coposu si Astra se află în imediata apropiere.
Pentru a ajunge aici de la gara, puteti merge pe jos 20min sau cu autobuzul 5 circa 10min
Locuri de parcare găsiți în parcarea supravegheata, sau pe străzile alăturate.
Cluj-Napoca, Pitești Street
NobleProg Cluj-Napoca, Strada Pitești 19, Cluj-Napoca, romania, 400124
ClujHUB has more rooms for events and training sessions, which can host from 4 to 80 people. These areas can be setup up to fit the companies need. The location is great, 10 minutes walk from the historical city center.
This instructor-led, live training in Transylvania (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 rapidly being integrated into decision-making processes across sectors such as defense, healthcare, finance, and infrastructure. As these systems gain greater independence and autonomy, there is an urgent need for robust ethical frameworks, governance mechanisms, and regulatory oversight to guide their design and deployment.
This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to explore the ethical, societal, and regulatory implications of deploying autonomous AI agents in real-world environments.
By the end of this training, participants will be able to:
Analyze the ethical risks and moral dilemmas posed by autonomous AI agents.
Evaluate governance frameworks and regulatory models relevant to high-stakes AI deployment.
Assess accountability, explainability, and transparency mechanisms in autonomous systems.
Develop strategies for aligning AI agent behavior with legal, ethical, and societal values.
Format of the Course
Interactive lecture and discussion.
Case studies and role-playing simulations.
Hands-on analysis of governance models and ethical frameworks.
Course Customization Options
To request a customized training for this course, please contact us to arrange.
AI-driven automation merges the flexibility of no-code platforms with the intelligence of large language models and autonomous agents to build scalable, intelligent systems.
This instructor-led, live training (available online or onsite) targets intermediate-level professionals aiming to design, build, and optimize automation pipelines enhanced with AI decision-making, orchestration, and self-execution capabilities.
Upon completion of 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 applications that connect services and interpret data autonomously.
Understand, design, and deploy AI agents capable of goal-oriented action planning and execution.
Course Format
Interactive lectures and discussions.
Numerous exercises and practical activities.
Hands-on implementation in a live-lab environment.
Course Customization Options
For customized training requests, please contact us to arrange.
This instructor-led, live training in Transylvania (online or onsite) is designed for intermediate-level AI developers, security experts, and compliance officers who aim to create and deploy secure AI agents while tackling ethical issues and enhancing robustness.
Upon completing this training, participants will be able to:
Grasp the security risks and ethical challenges inherent in AI agent development.
Put into practice security-first design principles for AI models.
Utilize adversarial robustness techniques to defend AI agents against attacks.
Guarantee adherence to ethical AI guidelines and regulatory standards.
Edge & Lightweight Agents is a practical course focused on deploying agentic AI workloads on resource-constrained devices. Participants learn to build, 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.
This instructor-led, live training in Transylvania (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 Transylvania (online or onsite) is designed for developers and designers at beginner to intermediate levels who aim to understand and build AI-powered personal assistants for diverse applications.
Upon completion of this training, participants will be able to:
Grasp the core principles underlying AI-powered personal assistants.
Master the fundamentals of integrating language models with smart assistants.
Build and customize a personal assistant using AI frameworks and tools.
Deploy personal assistants for real-world applications across various industries.
This instructor-led, live training in Transylvania (available online or on-site) targets advanced AI engineers, enterprise software developers, and business leaders aiming to customize and deploy LLM-based AI agents for enterprise solutions.
By the conclusion 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 Transylvania (online or onsite) is aimed at advanced-level robotics engineers, AI researchers, and automation specialists who wish to develop AI-driven autonomous robotic systems for complex tasks and human-AI collaboration.
By the end of this training, participants will be able to:
Understand the role of AI agents in robotic decision-making and automation.
Implement AI-driven navigation and obstacle avoidance.
Develop human-AI collaborative robotic systems.
Deploy AI-powered perception and control systems in robots.
This program investigates the design, coordination, and implementation of multi-agent systems (MAS) utilizing Python. Participants will acquire the skills to construct agents capable of communication, collaboration, and adaptation to achieve common goals within complex, dynamic environments.
This instructor-led, live training (available online or onsite) targets advanced professionals interested in designing and implementing multi-agent systems for intelligent automation, simulation, and decision-making applications.
Upon completion of this training, participants will be able to:
Grasp the architecture and principles underlying multi-agent systems.
Create agents capable of communication, coordination, and negotiation.
Establish distributed environments for agent interactions.
Apply reinforcement learning and planning techniques within multi-agent contexts.
Simulate both cooperative and competitive agent behaviors.
Design hybrid workflows that integrate humans with intelligent agents.
This instructor-led live training in Transylvania (offered online or on-site) targets intermediate-level financial professionals, risk analysts, and AI engineers interested in developing and deploying AI-driven solutions for financial automation and fraud detection.
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Upon completing this training, participants will be able to:
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Grasp the role of AI in automating financial processes and detecting fraud.
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Develop AI models specifically for identifying fraudulent transactions.
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Utilize machine learning techniques for real-time risk evaluation.
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This instructor-led, live training in Transylvania (online or onsite) is designed for beginner to intermediate-level customer service professionals, chatbot developers, and automation teams aiming to implement AI-driven solutions for customer support and service automation.
By the end of this training, participants will be able to:
Grasp the fundamentals of AI-powered customer support.
Develop and integrate AI chatbots to manage customer inquiries.
Utilize NLP and machine learning to improve chatbot interactions.
Deploy AI agents in real-world customer service applications.
This instructor-led, live training in Transylvania (online or onsite) is designed for intermediate to advanced healthcare professionals and AI developers looking to deploy AI-driven healthcare solutions.
By the end of this training, participants will be able to:
Grasp the role of AI agents in healthcare and diagnostics.
Create AI models for medical image analysis and predictive diagnostics.
Integrate AI with electronic health records (EHR) and clinical workflows.
Ensure adherence to healthcare regulations and ethical AI practices.
This instructor-led, live training in Transylvania (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 tasks, and agentic applications.
This instructor-led live training, available either online or on-site, targets intermediate to advanced professionals seeking to build, deploy, and manage AI agents using Mistral’s Medium 3, Le Chat Enterprise, and Devstral models.
Upon completion of this course, participants will be equipped to:
Grasp the architecture and capabilities of Mistral Medium 3, Le Chat Enterprise, and Devstral.
Design and implement AI agents tailored for enterprise and developer use cases, leveraging Mistral models.
Integrate coding systems, connectors, and enterprise data into agent workflows.
Optimize performance, manage costs, and ensure compliance for agents powered by Mistral.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical practice.
Hands-on implementation within a live laboratory environment.
Course Customization Options
For customized training requests, please contact us to arrange suitable options.
Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to build, integrate, and manage agent workflows.
Delivered by an expert instructor, this live training (available online or onsite) targets intermediate-level backend engineers, platform engineers, and ML engineers who aim to implement and orchestrate autonomous agents using Python tooling and APIs.
Upon completing this training, participants will be able to:
Set up and configure Python-based environments suitable for agentic systems.
Leverage popular agent SDKs like LangChain and AutoGen to develop functional agents.
Integrate tools and APIs to expand agent capabilities.
Orchestrate multi-agent workflows and establish communication patterns.
Apply best practices for debugging, testing, and maintaining agentic codebases.
Format of the Course
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 customized training for this course, please contact us to arrange your session.
This course provides practical engineering techniques for designing, building, testing, and deploying 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.
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 Transylvania (online or onsite) is aimed at advanced professionals who wish to master the techniques for deploying and managing AI agents in production environments.
By the end of this training, participants will be able to:
Design and implement scalable AI deployment pipelines.
Use tools like Docker and Kubernetes to containerize and orchestrate AI agents.
Monitor and optimize AI agents in production environments.
Implement CI/CD workflows for AI agent deployments.
Ensure compliance with security and data governance requirements.
This instructor-led, live training session in Transylvania (online or in-person) is designed for advanced AI professionals eager to master reinforcement learning techniques and apply them to train AI agents for solving complex problems.
Upon completion of this course, participants will be capable of:
Grasping the fundamental principles of reinforcement learning and Markov Decision Processes (MDPs).
Designing and deploying RL algorithms, including Q-Learning, SARSA, and Deep Q-Networks (DQN).
Leveraging frameworks such as OpenAI Gym and dedicated RL libraries for practical use cases.
Training AI agents to resolve real-world, multi-step decision-making challenges.
Managing common RL training hurdles, such as balancing exploration versus exploitation and ensuring convergence.
This instructor-led, live training in Transylvania (online or onsite) targets intermediate AI developers and automation experts aiming to integrate agentic capabilities into AI applications.
Upon completing this training, participants will be equipped to:
Grasp the core principles of agentic AI and autonomous decision-making.
Build goal-oriented AI agents using self-optimization methods.
Integrate collaboration among multiple agents to tackle complex challenges.
Improve interactions between AI and humans via personalized user experiences.
Deploy agentic AI models for practical, real-world use.
Designed for advanced AI professionals seeking to master the art of designing, building, and deploying MAS to tackle complex, real-world challenges, this instructor-led live training is available in Transylvania either online or onsite.
Upon completion of this training, participants will be equipped to:
Comprehend the fundamental principles underlying multi-agent system architectures.
Execute strategies for communication, coordination, and decision-making within MAS.
Utilize game theory to model agent interactions and resolve conflicts.
Employ frameworks such as JADE to develop scalable MAS solutions.
Manage challenges related to scalability, trust, and emergent behavior in MAS.
This instructor-led, live training in Transylvania (online or onsite) is designed for advanced professionals aiming to develop and optimize multi-agent systems through Agentic AI frameworks.
By the conclusion of this training, participants will be able to:
Understand the core principles of Agentic AI in multi-agent settings.
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.
This instructor-led, live training in Transylvania (online or onsite) is designed for intermediate-level business analysts, RPA developers, and AI professionals seeking to leverage AI agents for business process automation.
Upon completion of this training, participants will be able to:
Comprehend the role of AI agents in business process automation.
Identify 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/low-code environment for constructing grounded agents that integrate generative models with Retrieval-Augmented Generation (RAG). This enables teams to quickly develop agents that leverage enterprise data and search capabilities to deliver accurate, context-aware responses.
This instructor-led live training, available online or onsite, targets intermediate-level practitioners aiming to design, configure, and deploy intelligent agents using Vertex AI Agent Builder and RAG methodologies.
Upon completing this training, participants will be equipped to:
This instructor-led, live training in Transylvania (online or onsite) is designed for intermediate-level game developers and AI enthusiasts who wish to integrate AI agents into gaming applications effectively.
By the end of this training, participants will be able to:
Understand the role of AI agents in modern gaming.
Develop 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 create 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 the way DevOps teams automate critical tasks like change tracking, test generation, and alert triage. These technologies enable human-like collaboration and decision-making processes.
This instructor-led live training, available both online and onsite, is designed for advanced engineers seeking to architect and implement DevOps automation workflows driven by Large Language Models (LLMs) and multi-agent systems.
Upon completion of this training, participants will be capable of:
Integrating LLM-based agents into CI/CD pipelines for intelligent automation.
Automating test generation, commit analysis, and change summaries using agent technologies.
Coordinating multiple agents to triage alerts, generate responses, and deliver DevOps recommendations.
Constructing secure and maintainable agent-driven workflows using open-source frameworks.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical sessions.
Hands-on implementation within a live lab environment.
Customization Options
To arrange customized training for this course, please contact us.
This instructor-led, live training in Transylvania (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for decision-making in complex business and technical scenarios.
By the end of this training, participants will be able to:
Understand the principles of autonomous decision-making in AI.
Design and implement AI agents that operate with minimal human intervention.
Integrate Agentic AI into automation workflows and business systems.
Optimize AI-driven decision processes for efficiency and scalability.
Ensure compliance, security, and ethical considerations in AI autonomy.
This instructor-led, live training in Transylvania (online or onsite) targets intermediate-level professionals eager to deepen their expertise in designing and developing autonomous agents for practical use cases.
Upon completion of this training, participants will be equipped to:
Grasp the foundational principles of autonomous agents.
Investigate real-world applications of autonomous AI agents.
Design, train, and deploy agents utilizing reinforcement learning techniques.
Integrate agents into current systems to facilitate automation and decision-making processes.
Navigate ethical considerations and challenges associated with deploying autonomous agents.
Devstral is an open-source framework engineered for the creation and execution of coding agents capable of interacting with code repositories, developer utilities, and APIs to boost engineering efficiency.
This instructor-led, live training (available online or on-site) targets intermediate to advanced ML engineers, developer-tooling teams, and Site Reliability Engineers (SREs) who aim to design, implement, and optimize coding agents using Devstral.
Upon completing this training, participants will be able to:
Establish and configure the Devstral environment for coding agent development.
Design agentic workflows for exploring and modifying codebases.
Integrate coding agents with developer tools and APIs.
Apply best practices for secure and efficient agent deployment.
Course Format
Interactive lectures and discussions.
Extensive exercises and practical application.
Hands-on implementation in a live laboratory environment.
Customization Options
To request tailored training for this course, please contact us to arrange the details.
This instructor-led, live training in Transylvania (online or onsite) is designed for beginner-level professionals who aim to understand how AI agents function and to build their own interactive chatbot systems.
By the conclusion 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.
This instructor-led, live training in Transylvania (online or onsite) targets 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 Transylvania (online or on-site) is aimed at beginner to intermediate-level developers and cloud practitioners who wish to use Alibaba Cloud to build AI agents that can automate tasks, answer questions, and integrate with business systems.
By the end of this training, participants will be able to: understand AI agent architecture on Alibaba Cloud, construct a simple agent workflow, connect an agent to enterprise knowledge and tools, and deploy and monitor an agent within a cloud environment.
This advanced, hands-on seminar is tailored for software engineers, architects, technical leads, engineering managers, and delivery teams seeking to understand how Artificial Intelligence can expedite the entire software delivery lifecycle, from initial requirements analysis to production-ready code.
This instructor-led, live training in Transylvania (online or onsite) is designed for developers and technical professionals at beginner, intermediate, and advanced levels who aim 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 the architecture of AI agents on Azure, create and configure a functional agent, link agents to business knowledge sources, and evaluate and prepare agents for deployment.
This instructor-led live training, conducted either online or on-site, is designed for software developers and DevOps teams aiming 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, perform tasks using natural language prompts, manage approval modes, and integrate with Git and CI pipelines.
This instructor-led, live training in Transylvania (online or onsite) is designed for developers who want 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 Transylvania (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 Transylvania (online or onsite) targets intermediate-level solution architects, AI engineers, developers, and technical product teams aiming to use Tencent ADP to build enterprise AI agents 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 Transylvania (online or onsite) targets developers and technical practitioners at beginner, intermediate, and advanced levels who wish to use Google Cloud to build AI agents that automate tasks, utilize tools, and process business data.
By the end of this training, participants will be able to explain AI agent concepts, build agents using Vertex AI, connect agents to external tools and data, and deploy agents for business use cases.
This instructor-led, live training in Transylvania (online or onsite) is aimed at developers and DevOps professionals who wish to use Hermes Agent to automate development tasks, manage infrastructure, and build persistent AI workflows.
By the end of this training, participants will be able to install and configure Hermes Agent, interact with it across multiple platforms, use 40+ built-in tools, and deploy on various backends.
This instructor-led, live training in Transylvania (online or onsite) is designed for business users, operations teams, and technical professionals who intend to use Hermes Agent to automate work, create reusable AI-driven processes, and boost team productivity.
By the end of this training, participants will be able to: understand Hermes Agent fundamentals, set up and utilize core features, construct practical workflows, and apply best operational practices.
This instructor-led live training in Transylvania (online or onsite) is designed 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 Transylvania (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-augmented workflows, and apply security and governance controls for regulated environments.
This course provides a practical, hands-on approach to building local AI and LLM-powered applications using LangChain and CrawAI. Participants will investigate data analytics, machine learning, and model training techniques before progressing to LLM-based application development.
The course encompasses essential topics such as multi-model AI applications, no/low-code AI development, Retrieval-Augmented Generation (RAG), agentic AI, and AI automation with CrawAI. Participants will also learn to construct AI chatbots, AI-powered knowledge bases, and offline/local AI models to guarantee privacy and efficiency.
This instructor-led, live training in Transylvania (online or onsite) is aimed at backend developers who wish to build MCP-compatible tool servers and integrate them with agent clients.
By the end of this training, participants will be able to implement MCP servers, connect them to Claude Code and OpenClaude, switch transports, and maintain an internal tool registry.
This instructor-led, live training in Transylvania (online or onsite) is aimed at beginner, intermediate, or advanced AI professionals who wish to use MCP to connect AI assistants with external tools, data, and enterprise services.
By the end of this training, participants will be able to: explain MCP concepts, identify key architecture components, set up a basic integration, and apply security good practices.
This instructor-led, live training in Transylvania (online or onsite) is designed for beginner to intermediate developers and technical teams who wish to use OpenAI APIs to build AI agents that can reason, utilize tools, and perform multi-step tasks.
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 Transylvania (online or onsite) is aimed at intermediate-level / advanced-level developers and technical professionals who wish to use OpenClaw to build and run practical AI agents that automate work through chat and tool integrations.
By the end of this training, participants will be able to: install and configure OpenClaw, connect an LLM provider, use and adapt skills for automation, and apply basic security and operational guardrails.
This instructor-led live training, held online or onsite, is designed for senior developers who want to utilize Pi to build lightweight, customizable terminal agent workflows.
By the end of the course, participants will know how to install Pi, extend it with TypeScript skills, adapt workflows to meet team standards, and share extensions via npm.
This instructor-led live training in Transylvania (online or onsite) is aimed at developers who wish to use Pi Coding Agent to generate code, review changes, and streamline terminal-based development workflows.
By the end of this training, participants will be able to explain Pi Coding Agent concepts, effectively set up and use the tool, apply it to practical coding tasks, and adopt safe team workflows.
This instructor-led, live training in Transylvania (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.
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Testimonials (5)
It triggered awareness about working with complex topics and the way, how to start.
Victoria Schmid - Medeo Investment AG
Course - Getting Started with Manus AI
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
practical exercises
Daniel - Facultatea S.A.I.A.P.M.
Course - Agentic AI in Multi-Agent Systems
I liked that he constantly provided examples but also offered time for individual work on what he presented.
Iacob Giorgel
Course - Agentic AI Unleashed: Crafting LLM Applications with AutoGen
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