Agentic AI Training in Dartmouth

This live training in Dartmouth explores how agentic AI reshapes organizational workflows, talent strategies, and job design. Ideal for intermediate professionals, it covers autonomous decision-making, enterprise readiness, and governance frameworks to ensure responsible, compliant AI adoption.

This instructor-led bootcamp in Dartmouth offers a hands-on journey to build autonomous AI agents in Python. Participants complete five progressive projects covering design patterns, API orchestration, and multi-agent workflows, moving from theory to real-world deployment.

This practical course in Dartmouth guides you through deploying agentic AI on resource-constrained devices. Learn to build, optimize, and manage lightweight agents for local reasoning using Python, TensorFlow Lite, and PyTorch Mobile, enhancing speed, privacy, and reliability.

This instructor-led, live training in Dartmouth introduces agentic AI, covering prompt engineering, design patterns, and responsible use. Participants learn to build simple agent workflows with Python, integrate tools, and implement safety practices for effective, safe, and scalable autonomous systems.

This instructor-led, live training in Dartmouth guides intermediate professionals on designing and scaling agentic AI for business automation. Learn to map workflows, integrate tools, and build practical use cases in customer service, supply chain, and marketing, ensuring measurable impact.

This live training in Dartmouth guides advanced professionals to design and implement multi-agent systems using Python. It covers agent coordination, reinforcement learning, and distributed computing with frameworks like Mesa and Ray, ending in a hands-on capstone project.

This instructor-led training in Dartmouth covers reinforcement learning and decision-making for agentic AI. Learners implement DQN, PPO, and A3C using Python, model environments with OpenAI Gym, and integrate these techniques into robotics and planning systems for real-world adaptive behavior.

This live training in Dartmouth equips advanced professionals with the skills to scale and operationalize agentic AI systems in production. It covers MLOps, observability, and cost control, enabling the design of resilient, observable, and cost-optimized pipelines for large-scale deployments.

This instructor-led live training in Dartmouth helps BI professionals modernize legacy systems with WrenAI. You will evaluate existing environments, plan migrations to conversational analytics, and lead change management efforts to ensure successful adoption and business impact.

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

This instructor-led, live training in Dartmouth focuses on practical Python implementation for autonomous AI agents. It covers modern SDKs like LangChain and AutoGen, enabling engineers to build, connect, and orchestrate complex agent workflows with confidence.

This instructor-led training in Dartmouth helps finance professionals use WrenAI to model KPIs and design regulatory-aware dashboards. Participants gain practical skills in integrating data sources, ensuring audit compliance, and building risk management reports for effective decision-making.

This instructor-led live training in Dartmouth covers practical Python techniques for building autonomous agents, including agent loops, tool integrations, memory management, orchestration, and safety controls. Ideal for ML engineers, it focuses on deploying robust, production-ready agents.

This instructor-led training in Dartmouth equips advanced professionals with essential skills for WrenAI quality assurance. Participants will learn to evaluate NL-to-SQL accuracy, apply prompt tuning, and implement observability frameworks. Ideal for ensuring enterprise-grade reliability and compliance.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at intermediate-level AI developers and automation specialists who wish to integrate agentic capabilities into AI-powered applications.

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

• Understand the principles of agentic AI and autonomous decision-making.
• Implement goal-driven AI agents with self-optimization techniques.
• Integrate multi-agent collaboration for complex problem-solving.
• Enhance AI-human interaction through adaptive user experiences.
• Deploy agentic AI models in real-world applications.

This instructor-led live training in Dartmouth helps operations professionals master WrenAI Spreadsheets and the Metrics Library. Learn to build AI-powered reports, connect live data, and streamline workflows to accelerate operational analytics and drive efficient business reporting.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at advanced-level professionals who wish to develop and optimize multi-agent systems using Agentic AI frameworks.

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

• Understand the principles of Agentic AI in multi-agent environments.
• 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 Dartmouth (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for enterprise-scale automation and strategic AI adoption.

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

• Understand 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 Dartmouth (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 Dartmouth (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 Dartmouth (online or onsite) is aimed at beginner-level professionals who wish 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 5-day course in Dartmouth equips finance professionals with advanced analytics, AI-assisted Python, and agentic AI skills. Learn to build intelligent dashboards, streamline GL operations, and design autonomous workflows for financial analysis, reporting, and strategic decision support.

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 moving from research demos to production systems that act autonomously across text, image, speech, and tool-driven workflows, raising the bar for engineering rigor, adversarial robustness, and regulatory accountability. This instructor-led training takes advanced practitioners through the full agent lifecycle, from architecting single and multi-agent systems to integrating multi-modal perception and orchestrating coordinated agent behavior through modern frameworks. Hands-on labs in Python build progressively toward a production-grade multi-agent system, which participants then stress-test using adversarial techniques and the Adversarial Robustness Toolbox. The course closes with NIST AI RMF, ISO/IEC 42001, EU AI Act, and GDPR alignment, secure deployment, monitoring, and incident response, so participants leave able to ship agents that are capable, defensible, and compliant.

This instructor-led, live training in Dartmouth (online or onsite) is aimed at beginner-level / intermediate-level developers and cloud practitioners who wish to use Alibaba Cloud to build AI agents that can automate tasks, answer questions, and connect with business systems.

By the end of this training, participants will be able to: understand AI agent architecture on Alibaba Cloud, build a simple agent workflow, connect an agent to enterprise knowledge and tools, deploy and monitor an agent in a cloud environment.

This instructor-led, live training in Dartmouth is aimed at intermediate-level developers who wish to design, build and test AI agents with the Claude API and the Agent SDK.

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

• Call the Messages API with system prompts, structured output and streaming
• Define tools and implement a reliable tool-use loop
• Connect agents to external systems through MCP servers
• Build and run agents with the Claude Agent SDK, including permissions and subagents
• Reduce cost and latency with prompt caching and sensible context handling
• Test, log and monitor agent behavior with a small evaluation set

Claude Cowork takes over whole tasks such as research, document preparation and file work instead of answering one prompt at a time. This course teaches how to write good assignments, check the plan and review the results. Participants hand over three real tasks and set up a scheduled task.

This instructor-led, live training in Dartmouth is aimed at: Knowledge workers, assistants, project and department leads who want to hand over entire tasks to Claude instead of chatting step by step.

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

• Understand the difference between chat and delegated work in Cowork
• Formulate assignments with goal, material, limits and acceptance criteria
• Have documents, spreadsheets and presentations created from a folder
• Hand over research from the question to the finished report
• Use plugins, skills and connectors in Cowork
• Define approval points, backups and safe folder access

Format of the Course

• Duration: 1 day (7 hours)
• Interactive training with a trainer, discussion and hands-on exercises on the participants' own use cases
• Outcome, Day 1: Each participant has handed over three real tasks to Cowork, reviewed the results and set up a scheduled task.

Course Customization Options

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

Agents allow teams to answer knowledge questions and support document processes in a controlled way. This two-day course covers Agent Builder on day 1 and Copilot Studio with approval steps and test cases on day 2. Participants leave with a tested knowledge agent and a draft for a Studio agent.

This instructor-led, live training in Dartmouth is aimed at: Key users, AI champions and department leads who want to build their own Copilot agents for knowledge questions and document processes.

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

• Decide when Copilot Chat is enough and when an agent makes sense
• Build a knowledge agent in Agent Builder with audience, knowledge sources and limits
• Understand the structure of an agent in Copilot Studio and create a first agent
• Break down document processes into reviewable steps with human approval
• Test agents with test cases and acceptance criteria
• Classify roles, permissions, licenses and operation

Format of the Course

• Duration: 2 days (7 hours each)
• Interactive training with a trainer, discussion and hands-on exercises on the participants' own use cases
• Outcome, Day 1: Each participant has a tested knowledge agent and a tool map for their own work cases.
• Outcome, Day 2: Each participant has a draft for a Studio agent with approval, two tested process cases and a roadmap for their own use cases.

Course Customization Options

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

An assistant on company documents can answer questions about policies, manuals and processes and name the source. This course shows how to prepare documents, choose a platform, build the agent without code and measure its answers with a question catalog. Participants also write a maintenance plan.

This instructor-led, live training in Dartmouth is aimed at: Teams, knowledge owners and key users who want to provide answers from their own documents, policies and manuals.

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

• Understand how AI answers from documents (RAG explained simply) and where the limits are
• Prepare documents so that answers are correct
• Choose the right platform for a knowledge agent
• Build and share a knowledge agent without code
• Verify answers with a question catalog and source references
• Define maintenance, roles and currency of content in operation

Format of the Course

• Duration: 1 day (7 hours)
• Interactive training with a trainer, discussion and hands-on exercises on the participants' own use cases
• Outcome, Day 1: Each participant has a shared knowledge agent on their own documents, a measured hit rate and a maintenance plan.

Course Customization Options

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

Langdock brings several AI models, assistants, company knowledge and workflows into one platform for the company. This course covers daily use in chat, building and sharing assistants, connecting knowledge sources and setting up a workflow with human approval. It also covers rules for data, roles and rollout.

This instructor-led, live training in Dartmouth is aimed at: Departments and key users in companies that use or are introducing Langdock as a central AI platform.

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

• Operate Langdock confidently, including chat, models, assistants, knowledge and workflows
• Choose a suitable model for each task
• Build assistants with instructions and company knowledge and share them in the team
• Connect SharePoint, OneDrive and other sources as a knowledge base
• Set up a simple workflow with human approval
• Define rules for data, roles and approvals in the company

Format of the Course

• Duration: 2 days (7 hours each), also available as 4 half days online
• Interactive training with a trainer, discussion and hands-on exercises on the participants' own use cases
• Outcome, Day 1: Each participant has a template, a knowledge folder and a shared assistant for their own area.
• Outcome, Day 2: Each participant has a running workflow with approval, a connected knowledge source and a plan for the next 30 to 60 days.

Course Customization Options

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

This instructor-led, live training in Dartmouth is aimed at intermediate-level professionals who wish to automate business processes and build their first AI agent with Make.

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

• Design no-code workflows in Make with triggers and webhooks.
• Connect an AI agent to their data within a flow.
• Automate a real process end to end, with error handling and monitoring.

A personal AI agent can sort email, plan appointments, prepare briefings and run routines such as a morning overview. This one-day course shows how to set it up with a personal context, connectors and clear rules for approval and data protection. Participants leave with a working agent and two running routines.

This instructor-led, live training in Dartmouth is aimed at: Professionals, assistants, project managers and self-employed people who want to set up a personal AI agent for their own work.

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

• Understand what a personal AI agent can take over and what it cannot
• Build a personal context with profile, instructions and notes
• Organize email and calendar with AI without giving up control
• Prepare appointments and conversations with automatic briefings
• Set up routines such as a morning overview and a weekly review
• Define approvals, data protection and limits for the own agent

Format of the Course

• Duration: 1 day (7 hours)
• Interactive training with a trainer, discussion and hands-on exercises on the participants' own use cases
• Outcome, Day 1: Each participant has a set-up personal agent with a profile, a connected mailbox and calendar, and two running routines.

Course Customization Options

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

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

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

• Organize 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