Agentic AI Training in Manaus

This live training in Manaus examines the way agentic AI is redefining organizational workflows, talent strategies, and job design. Geared toward intermediate professionals, the course covers autonomous decision-making, enterprise preparedness, and governance frameworks essential for ensuring responsible and compliant AI adoption.

This instructor-led bootcamp in Manaus provides a hands-on pathway to developing autonomous AI agents in Python. Participants will complete five staged projects covering design patterns, API orchestration, and multi-agent workflows, progressing from theoretical understanding to real-world deployment.

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

This live, instructor-led program in Manaus provides an introduction to agentic AI, detailing prompt engineering, architectural patterns, and ethical application. Participants will learn to construct simple agent workflows in Python, integrate external tools, and apply safety protocols to create autonomous systems that are effective, secure, and scalable.

This live, instructor-led training in Manaus empowers intermediate professionals to design and scale agentic AI solutions for business automation. Participants will learn to map workflows, connect tools, and develop practical applications in customer service, supply chain, and marketing, all while ensuring quantifiable business impact.

This live training in Manaus empowers advanced professionals to design and build multi-agent systems using Python. The curriculum covers agent coordination, reinforcement learning, and distributed computing through frameworks such as Mesa and Ray, culminating in a practical, hands-on capstone project.

This instructor-led training in Manaus focuses on reinforcement learning and decision-making for agentic AI. Learners will implement DQN, PPO, and A3C using Python, model environments with OpenAI Gym, and integrate these methodologies into robotics and planning systems to achieve real-world adaptive behavior.

This live training on Manaus empowers advanced professionals with the expertise required to scale and operationalize agentic AI systems in production. It comprehensively covers MLOps, observability, and cost governance, enabling the creation of resilient, observable, and cost-efficient pipelines for large-scale deployments.

This live, instructor-led training in Manaus guides BI professionals in transforming legacy systems with WrenAI. Participants will learn to assess current environments, strategize the move to conversational analytics, and spearhead change management initiatives to secure successful adoption and measurable business impact.

This instructor-led training in Manaus addresses governance, identity management, and red-teaming for agentic AI systems. Advanced practitioners will learn to design secure deployments, implement least-privilege access, and execute adversarial testing to mitigate real-world threats in production environments.

This live, instructor-led training in Manaus offers a practical approach to Python development for autonomous AI agents. It covers modern SDKs like LangChain and AutoGen, empowering engineers to build, connect, and orchestrate complex agent workflows with confidence.

This instructor-led training in Manaus equips finance professionals with the skills to use WrenAI for KPI modeling and the creation of regulatory-aware dashboards. Participants will gain practical expertise in integrating data sources, maintaining audit compliance, and developing risk management reports to support informed decision-making.

This instructor-led live training in Manaus focuses on practical Python techniques for creating autonomous agents, covering agent loops, tool integrations, memory management, orchestration, and safety controls. Ideally suited for ML engineers, it emphasizes deploying robust, production-ready agents.

This instructor-led, live training in Manaus (online or onsite) targets intermediate-level AI developers and automation specialists looking to integrate agentic capabilities into AI-powered applications.

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

• Comprehend the principles of agentic AI and autonomous decision-making.
• Build goal-driven AI agents using self-optimization techniques.
• Integrate multi-agent collaboration for tackling complex problems.
• Improve AI-human interaction through adaptive user experiences.
• Deploy agentic AI models in real-world applications.

This instructor-led, live training in Manaus (available online or onsite) targets advanced professionals aiming to develop and optimize multi-agent systems using Agentic AI frameworks.

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

• Grasp the core principles of Agentic AI within multi-agent environments.
• Create AI-driven agents capable of autonomous interaction.
• Implement reinforcement learning techniques to enable adaptive AI behavior.
• Optimize both collaboration and competition among multiple agents.
• Apply Agentic AI solutions in robotics, gaming, and enterprise automation.

This instructor-led, live training in Manaus (online or onsite) is designed for advanced-level professionals who want to harness Agentic AI for enterprise-scale automation and strategic AI adoption.

Upon completing this training, participants will be able to:

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

This instructor-led, live training in Manaus (online or onsite) is designed for advanced professionals aiming to utilize Agentic AI for decision-making in complex business and technical scenarios.

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

• Grasp the fundamental principles of autonomous decision-making within AI.
• Design and deploy AI agents that function with minimal human oversight.
• Seamlessly integrate Agentic AI into automation workflows and business systems.
• Optimize AI-driven decision processes to enhance efficiency and scalability.
• Maintain compliance, security, and ethical standards in AI autonomy.

This instructor-led, live training in Manaus (online or onsite) is aimed at intermediate-level AI engineers, ML researchers, and developers who wish to build and implement Agentic AI systems in real-world applications.

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

• Understand the core principles of Agentic AI systems.
• Implement AI agents capable of autonomous reasoning and action.
• Integrate Agentic AI with APIs and third-party services.
• Optimize multi-agent interactions for complex tasks.
• Address ethical, security, and scalability challenges in Agentic AI.

This instructor-led, live training in Manaus (online or onsite) targets beginner-level professionals seeking to understand the fundamental principles of Agentic AI, its capabilities, and its potential impact on industries.

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

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

This five-day course in Manaus empowers finance professionals with skills in advanced analytics, AI-assisted Python, and agentic AI. Participants will learn to construct intelligent dashboards, optimize GL operations, and design autonomous workflows to enhance financial analysis, reporting, and strategic decision-making.

This one-day course provides software engineers, technical leads and development teams with a practical framework for working effectively with AI coding agents in real-world software projects. Rather than focusing on prompting techniques alone, the course explores the complete agent ecosystem, including context engineering, reusable workflows, MCP (Model Context Protocol) integrations, feedback loops, security and organisational adoption.

AI agents are transitioning from research demonstrations to autonomous production systems capable of operating across text, image, speech, and tool-driven workflows. This shift demands heightened engineering rigor, robustness against adversarial attacks, and strict regulatory accountability. This instructor-led training guides advanced practitioners through the entire 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 progressive Python-based hands-on labs, participants build a production-grade multi-agent system, which is then stress-tested using 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 strategies, monitoring protocols, and incident response plans, empowering participants to deliver agents that are capable, defensible, and compliant.

This instructor-led live training in Manaus (available online or onsite) is tailored for developers and cloud practitioners at beginner to intermediate levels who wish to utilize Alibaba Cloud to build AI agents capable of automating tasks, answering inquiries, and integrating with business systems.

By the end of this training, participants will understand the architecture of AI agents on Alibaba Cloud, construct a simple agent workflow, connect agents to enterprise knowledge bases and tools, and deploy and monitor agents within a cloud environment.

This live, instructor-led training in Manaus is designed for intermediate developers who intend to design, construct, and validate AI agents utilizing the Claude API and the Agent SDK.

Following the completion of this course, participants will be able to:

• Interact with the Messages API using system prompts, structured outputs, and streaming
• Create tools and execute a reliable tool-use loop
• Link agents to external platforms via MCP servers
• Implement and deploy agents with the Claude Agent SDK, including permission controls and subagent management
• Minimize costs and latency by leveraging prompt caching and strategic context handling
• Verify, record, and monitor agent performance using a concise evaluation set

Claude Cowork is designed to handle complete workflows—such as in-depth research, document drafting, and file management—rather than responding to individual prompts in isolation. This course guides you through the process of crafting effective assignments, monitoring execution plans, and evaluating final outputs. Throughout the session, participants will delegate three practical tasks and configure an automated scheduled workflow.

This live, instructor-led training in Manaus is tailored for knowledge workers, administrative assistants, and project or department leaders seeking to delegate entire projects to Claude rather than managing them through step-by-step chat interactions.

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

• Distinguish between conversational chat and autonomous delegated work within Cowork
• Structure assignments by defining objectives, required materials, constraints, and success criteria
• Generate documents, spreadsheets, and presentations directly from organized folders
• Delegate research processes from initial inquiry to the delivery of a finalized report
• Leverage plugins, specific skills, and connectors within the Cowork environment
• Establish approval checkpoints, backup protocols, and secure folder access controls

Course Format

• Duration: 1 day (7 hours)
• Interactive training sessions featuring live instructor guidance, group discussions, and hands-on exercises applied to participants' real-world use cases
• Key Outcome: By the end of Day 1, each participant will have delegated three real-world tasks to Cowork, analyzed the resulting outputs, and implemented a scheduled task.

Course Customization Options

• To request a tailored version of this course, please contact our team to discuss your specific requirements.

Teams can leverage agents to handle knowledge queries and streamline document workflows within a controlled framework. This two-day program focuses on Agent Builder during the first day and transitions to Copilot Studio on the second day, emphasizing approval workflows and rigorous testing. Participants will conclude the course with a fully tested knowledge agent and a comprehensive draft for a Studio-based agent.

This live, instructor-led training in Manaus is designed for key users, AI champions, and department leaders aiming to develop custom Copilot agents for addressing knowledge questions and managing document processes.

Upon completion, participants will have the capability to:

• Determine the appropriate scenario for using Copilot Chat versus deploying a dedicated agent.
• Develop a knowledge agent within Agent Builder, defining specific audiences, knowledge sources, and operational limits.
• Comprehend the architectural structure of agents in Copilot Studio and develop an initial implementation.
• Decompose document workflows into manageable, reviewable steps that incorporate human approval mechanisms.
• Evaluate agent performance using defined test cases and acceptance criteria.
• Categorize roles, permissions, licensing requirements, and operational responsibilities.

Course Structure

• Duration: Two days, each lasting seven hours.
• Interactive sessions featuring trainer-led discussions and hands-on exercises focused on participants' specific use cases.
• Day 1 Outcome: Participants will possess a validated knowledge agent and a strategic tool map tailored to their professional needs.
• Day 2 Outcome: Participants will finalize a draft Studio agent with integrated approvals, two tested process scenarios, and a strategic roadmap for future implementations.

Customization Opportunities

• Contact us to discuss and arrange customized training tailored to your specific requirements.

A company-specific assistant can address inquiries regarding policies, manuals, and processes, clearly citing the source material. This course guides you through preparing documents, selecting a suitable platform, and developing the agent using a no-code methodology. It also covers measuring response accuracy using a question catalog, while participants develop a comprehensive maintenance strategy.

This live, instructor-led training in Manaus is designed for teams, knowledge owners, and key users looking to provide accurate answers derived from their internal documents, policies, and manuals.

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

• Grasp the mechanics of AI-generated answers from documents (a simplified explanation of RAG) and identify their limitations
• Optimize document preparation to ensure answer accuracy
• Select the most appropriate platform for a knowledge agent
• Construct and distribute a knowledge agent without writing code
• Validate responses using a question catalog and source citations
• Establish maintenance protocols, define roles, and manage content currency in operational settings

Course Format

• Duration: 1 day (7 hours)
• Interactive sessions led by a trainer, featuring discussions and hands-on exercises focused on participants' specific use cases
• Day 1 Outcome: Each participant will possess a shared knowledge agent built on their own documents, a measured hit rate, and a defined maintenance plan.

Customization Options

• To tailor this training to your specific needs, please reach out to us to arrange a customized session.

Langdock unifies various AI models, assistants, company knowledge, and workflows onto a single enterprise platform. This course addresses daily chat usage, the development and sharing of assistants, the integration of knowledge sources, and the setup of workflows that include human approval. It also covers policies regarding data, roles, and deployment.

This instructor-led, live training in Manaus is designed for: Departments and key users within organizations that are currently using or adopting Langdock as their central AI platform.

Upon completing this training, participants will be able to:

• Proficiently operate Langdock, covering chat, models, assistants, knowledge management, and workflows
• Select the appropriate model for specific tasks
• Develop assistants equipped with instructions and corporate knowledge, and share them across the team
• Integrate SharePoint, OneDrive, and other sources as a knowledge base
• Configure a simple workflow that includes human approval
• Establish rules for data handling, roles, and approvals within the organization

Course Format

• Duration: 2 days (7 hours each), with the option to schedule it as 4 half-days online
• Interactive training featuring a trainer, discussions, and hands-on exercises focused on participants' specific use cases
• Day 1 Outcome: Each participant will possess a template, a knowledge folder, and a shared assistant tailored to their area of responsibility.
• Day 2 Outcome: Each participant will have a functional workflow with approval capabilities, a connected knowledge source, and a 30 to 60-day plan.

Course Customization Options

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

This live, instructor-led training in Manaus is tailored for intermediate professionals who want to streamline business processes and create their first AI agent using Make.

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

• Design no-code workflows in Make using triggers and webhooks.
• Link an AI agent to their data within a flow.
• Automate a genuine process from start to finish, including error handling and monitoring.

A personal AI agent can streamline email management, schedule appointments, draft briefings, and execute recurring tasks like a daily morning summary. This one-day course guides you through setting up an agent tailored to your personal context, using connectors and establishing clear protocols for approval and data security. By the end, participants will have a fully functional agent with two active routines in place.

This live, instructor-led training in Manaus is designed for professionals, executive assistants, project managers, and entrepreneurs looking to implement a personal AI agent for their specific workflows.

Upon completion, participants will be able to:

• Distinguish between tasks a personal AI agent can automate and those requiring human oversight
• Create a personalized context using profiles, specific instructions, and notes
• Manage email and calendar with AI while maintaining full control
• Prepare for meetings and conversations using automatically generated briefings
• Establish automated routines, such as daily overviews and weekly reviews
• Configure approval workflows, data protection measures, and operational limits for the agent

Course Format

• Duration: 1 day (7 hours)
• Interactive sessions with an instructor, including discussions and hands-on exercises tailored to participants' use cases
• Day 1 Deliverable: A configured personal agent with a profile, connected email and calendar, and two operational routines

Customization Options

• Interested in a tailored version of this training? Please contact us to discuss specific requirements.

This live, instructor-led training in Manaus is designed for managers, assistants, and knowledge workers.

Upon completing this training, participants will be equipped to:

• Manage email and calendar using AI support
• Accelerate meeting preparation and research
• Configure a personal assistant tailored to individual preferences
• Safeguard personal and company data