The Agentic AI Systems Design Training Course by Oxford Training Centre is an advanced programme within the Artificial Intelligence (AI) category, designed to help professionals understand, design, and implement intelligent agentic AI systems. Participants will explore how autonomous AI agents perceive, reason, plan, collaborate, and execute complex tasks with minimal human intervention while maintaining effective governance and control.
The course covers the architecture of modern AI agents, multi-agent workflows, task planning, memory management, reasoning frameworks, orchestration strategies, and autonomy and oversight mechanisms. Through practical exercises and real-world case studies, learners will develop the skills needed to build scalable, reliable, and secure agentic AI solutions for enterprise applications.
Objectives
By the end of this course, participants will be able to:
- Understand the principles and architecture of agentic AI systems.
- Design intelligent autonomous agents for business and enterprise applications.
- Build effective multi-agent workflows for collaborative AI problem-solving.
- Implement advanced task planning and decision-making strategies.
- Balance autonomy and oversight to ensure safe and responsible AI operations.
- Integrate memory, reasoning, and tool-use capabilities into AI agents.
- Evaluate agent performance, reliability, and scalability.
- Apply governance, monitoring, and risk management practices for autonomous AI systems.
- Develop practical agentic AI solutions using modern frameworks and platforms.
Target Audience
This course is suitable for:
- AI Engineers and Machine Learning Professionals
- Software Developers and Solution Architects
- Data Scientists
- AI Product Managers
- Digital Transformation Leaders
- Automation Engineers
- Innovation Managers
- Cloud and Enterprise Architects
- Technology Consultants
- Professionals interested in autonomous AI systems
Course Content
Module 1: Introduction to Agentic AI
- Fundamentals of agentic AI
- Evolution from traditional AI to autonomous agents
- Enterprise applications and industry trends
Module 2: AI Agent Architecture
- Agent components and system design
- Perception, reasoning, memory, and action
- Agent communication models
Module 3: Task Planning and Reasoning
- Intelligent task planning
- Goal decomposition and execution
- Decision-making and adaptive reasoning
Module 4: Multi-Agent Workflows
- Designing multi-agent workflows
- Agent collaboration and coordination
- Distributed task execution
- Conflict resolution strategies
Module 5: Autonomy and Oversight
- Principles of autonomy and oversight
- Human-in-the-loop systems
- Governance and accountability
- Monitoring autonomous behaviour
Module 6: Memory, Tools, and Knowledge Integration
- Short-term and long-term memory
- Retrieval-Augmented Generation (RAG)
- External tool integration
- Knowledge management
Module 7: Enterprise Agentic AI Design
- Workflow orchestration
- API integrations
- Security and compliance
- Scalable AI deployment
Module 8: Testing, Evaluation, and Optimisation
- Performance measurement
- Reliability and robustness testing
- Risk mitigation
- Continuous improvement strategies
Module 9: Capstone Project
- Design and develop a complete agentic AI solution
- Implement collaborative agent workflows
- Present and evaluate the final project
FAQs
1. What is the Agentic AI Systems Design Training Course?
It is an advanced training programme by Oxford Training Centre that teaches participants how to design, build, and manage agentic AI systems using modern architectures and autonomous AI techniques.
2. Who should attend this course?
The course is ideal for AI engineers, software developers, data scientists, solution architects, technology leaders, and professionals involved in AI transformation projects.
3. Does the course include multi-agent workflows?
Yes. Participants learn to design, coordinate, and optimise multi-agent workflows for complex enterprise automation and collaborative AI applications.
4. Will I learn task planning techniques?
Yes. The course covers intelligent task planning, reasoning strategies, workflow orchestration, and autonomous execution methods.
5. Does the course address AI governance?
Yes. The programme includes autonomy and oversight, governance frameworks, human supervision, monitoring, compliance, and responsible AI practices.
6. Are practical exercises included?
Yes. The course includes hands-on labs, real-world case studies, and a capstone project focused on designing and implementing agentic AI systems.
7. What skills will I gain after completing the course?
You will be able to design autonomous AI agents, implement multi-agent systems, manage task planning processes, integrate enterprise tools, and deploy secure, scalable agentic AI solutions.