Agentic AI & Digital Employees Diploma
A hands-on training programme that equips you to understand, design and connect AI agents to tools and data, and build automated workflows, multi-agent teams and digital employees — with a focus on governance, security and risk management.
6 Weeks
Price
3,000 AED
- When 5 people register through you: the person who referred them gets the course completely free.
- When 4 people register through you: AED 200 is deducted for each person.
- When 3 people register through you: AED 150 is deducted for each person.
- When 2 people register through you: AED 100 is deducted for each person.
To avail this offer, please contact us via WhatsApp +971 56 687 3653
Retired Military Discount
15% discount for retired military personnel and their children.
To receive the discount, please call or contact us via WhatsApp using the number shown to submit the required documents and have the discount applied.
Student Discount
10% discount for students at all educational levels.
To receive the discount, please call or contact us via WhatsApp using the number shown to submit the required documents and have the discount applied.
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Training Modules (6 Modules)
1 Introduction to Generative AI & AI Agentic, and From ChatGPT to Digital Employees
- Evolution of AI from traditional models to Generative AI
- Concept of AI Agentic and characteristics of agentic systems
- Difference between generation, reasoning, planning and execution
- Levels of autonomy in AI systems
- Organisational examples of agent use in business and services
- Difference between Chatbot, Copilot, AI Agent and Digital Employee
- From responding to users to initiating and executing tasks
- Concept of the digital employee and its role within hybrid teams
- Use-case scenarios in management, operations and customer service
- Boundaries of delegation and accountability between human and agent
- Applied activity: Analyse a traditional business process and identify where AI Agentic could be introduced
- Applied activity: Draft an initial job description for a digital employee serving a department or role of the participant's choice
2 AI Agent Components, and Prompt Engineering & Context Engineering for Agents
- Goal Definition and setting success criteria
- Planning and breaking a task into executable steps
- Memory: short-term and long-term memory, and task context
- Tools: using search engines, files, databases and APIs
- Execution Loop: observation, reasoning, action and verification
- Handling errors, retries and stopping execution
- Designing core System Instructions
- Formulating goals, constraints and output criteria
- Providing the agent with the right context without overloading it
- Building reusable Prompt templates for recurring tasks
- Managing context, memory and reference information
- Quality-assurance methods to reduce hallucination and task drift
- Applied activity: Draw an architecture diagram for an agent showing goal, memory, tools and execution sequence
- Applied activity: Build an instruction template for an administrative agent including role, goal, context, constraints and quality criteria
3 Designing Your First Practical AI Agent, and Automation Workflow for Enterprise Processes
- Turning a business problem into a buildable Use Case
- Defining inputs, outputs, tools and decision rules
- Building an initial workflow for the agent
- Testing normal and exceptional scenarios
- Measuring accuracy, time and output quality
- Documenting agent design and operating procedures
- Concept of Automation Workflow and the difference between traditional and agentic automation
- Analysing processes and identifying start, decision and end points
- Triggers and Actions
- Automating approvals, notifications, reports and follow-up
- Designing exception cases and escalation paths
- Measuring automation's impact on time, quality and cost
- Applied activity: Build an initial agent prototype that performs a real task such as summarising, processing a request, or sorting data
- Applied activity: Redesign a manual organisational process into an automated Workflow supported by a smart agent
4 Connecting AI Agents to Tools & Data, and Applications in HR & Management
- Concept of Tool Use and Function Calling
- Integration with email, files, spreadsheets and databases
- Principles of using APIs and connecting applications
- Retrieving organisational knowledge and connecting the agent to trusted sources
- Access permissions and credential management
- Verifying results before executing sensitive actions
- HR agents: enquiries, screening, onboarding and learning
- Management agents: reports, follow-up, meeting and correspondence management
- Customer-service agents: understanding, routing, resolving requests and escalation
- Selecting use cases by value, risk and feasibility
- Designing performance indicators to measure agent impact
- Applied activity: Design an integration scenario for an agent with three organisational sources or tools and define the required permissions
- Applied activity: Select a use case from HR, management or customer service and prepare a short project brief for it
5 Multi-Agent Systems & Building Agent Teams, and Designing Workforce AI in the Organisation
- Concept of Multi-Agent Systems and when more than one agent is needed
- Dividing roles among specialised agents
- Collaboration patterns: manager/executor, planner/critic, multiple experts
- Passing tasks, context and results between agents
- Resolving conflicts and preventing repetition and infinite loops
- Evaluating agent-team performance as a single system
- Concept of Workforce AI and the hybrid workforce
- Analysing jobs and tasks suited to automation or augmentation
- Defining digital roles, responsibilities and permissions
- Designing an Operating Model for digital employees
- Redistributing work between humans and AI
- Productivity, quality, cost and ROI indicators
- Applied activity: Design a team of 3–4 agents to execute a composite organisational process, defining each agent's role
- Applied activity: Prepare a Workforce AI map for a chosen department, including human employees, agents and their points of collaboration
6 Governance, Security, Risk & Human-in-the-Loop, and Final Project Presentation & Evaluation
- Principles of Agentic AI governance in organisations
- Privacy, data security and access permissions
- Operational risks: incorrect execution, hallucination, bias and tool misuse
- Decision logging (Auditability) and traceability
- Human-in-the-Loop and human approval/review checkpoints
- Classifying tasks by risk level and setting delegation controls
- Incident management, stopping an agent, and regaining control
- Presenting the targeted organisational problem or opportunity and the agent/agent-system design
- Presenting the Workflow, tools and data used, and the Human-in-the-Loop model
- Discussing applicability, scalability and improvement, and evaluating projects against technical, operational and ethical criteria
- Applied activity: Build a risk matrix and governance controls for an agent or digital employee designed by the participant
- Applied activity: Present the final project to a panel/trainer and receive feedback and an improvement plan
Outcomes
- Explain the concept of Agentic AI and distinguish between smart assistants, agents and digital employees
- Analyse and design the core components of an AI agent, including goal, planning, memory, tools and execution
- Formulate effective instructions and context for AI agents using Prompt Engineering and Context Engineering
- Build an agent prototype that performs a practical task and connect it to an organisational workflow
- Design AI-supported Workflow Automation processes
- Propose safe and controlled ways to connect agents to tools, data and applications
- Design a multi-agent system and coordinate roles among its members
- Prepare an integrated vision for a Workforce AI within a department or organisation
- Apply governance, security, risk-management and Human-in-the-Loop principles
- Prepare a scalable applied project demonstrating the expected organisational value of Agentic AI
Target Audience
- Administrative Leaders, Department & Digital Transformation Managers
- HR & Institutional Development Officers
- Operations, Quality & Project Management Staff
- Customer Service & Contact Centre Staff
- IT, Data & Automation Specialists
- Innovation, AI & Government/Institutional Transformation Teams
- Entrepreneurs, Business Owners & Consultants
- Researchers and professionals wishing to develop applied Agentic AI skills
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Certificate
- Retired Military Personnel Association
- Dubai Knowledge Authority
- ACTVET Certificate
- London College for Business Certificate
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Trainer
Noor Fahd Abbas
AI Consultant & Trainer
An AI consultant, trainer and researcher based in Dubai, specialising in artificial intelligence, digital transformation and innovation. She holds a degree in Mathematics from Damascus University and has delivered AI training programmes for government and private organisations across the UAE, including Dubai Customs and the Roads & Transport Authority. She is the published author of a book on human and artificial intelligence.
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