Introduction to Generative AI and AI Agents Training Workshop

Course overview

Generative artificial intelligence is changing how professionals create content, conduct research, analyze information, solve problems and deliver services. AI agents extend these capabilities by enabling AI systems to work toward defined goals, use approved tools, follow multi-step instructions and support business workflows with varying levels of human supervision.

This practical introductory workshop equips participants with the foundational knowledge and hands-on skills to use generative AI tools and understand how AI agents operate. Participants explore large language models, multimodal AI, prompt engineering, AI-powered research, document analysis, content generation, data interpretation, workflow automation and agent design.

Course objectives

• Explain the fundamentals of generative AI, large language models, multimodal AI and AI agents.
• Develop a practical use-case and implementation plan for applying generative AI or AI agents in a professional or organizational setting.
• Identify practical opportunities for AI-assisted automation while addressing privacy, security, bias, hallucinations, copyright and human oversight.
• Explain how AI agents plan tasks, use tools, maintain context and execute multi-step workflows under defined instructions and permissions.
• Apply generative AI tools to research, writing, summarization, document analysis, presentations and workplace problem-solving.
• Use effective prompt-engineering techniques to improve the accuracy, relevance and quality of AI-generated outputs.

Who should attend

Course content

• Module 1: Foundations of Artificial Intelligence and Generative AI Artificial intelligence versus traditional automation, machine learning and deep learning fundamentals, predictive AI versus generative AI, what generative AI can and cannot do, text gener
• Module 2: Understanding Large Language Models and AI Assistants What large language models are, how AI models generate responses, tokens and context windows, model training and inference at a conceptual level, AI assistants and conversational interfaces,
• Module 3: Generative AI Tools and Their Applications Conversational AI tools, AI-powered web research, document and PDF analysis, writing and editing assistants, presentation generation, spreadsheet and data-analysis assistance, image generation, meeting
• Module 4: Prompt Engineering and Effective AI Communication Anatomy of an effective prompt, defining roles and objectives, providing context and source material, specifying audience and tone, constraints and output formats, step-by-step prompting, few-sho
• Module 5: AI for Research, Writing and Knowledge Management Research planning and question formulation, summarizing long documents, extracting key findings, comparing reports and policies, drafting proposals and concept notes, generating meeting agendas a
• Module 6: AI for Data Analysis and Decision Support Preparing structured information for analysis, asking questions about spreadsheets, identifying patterns and anomalies, interpreting charts and tables, generating analytical summaries, comparing scenario
• Module 7: Understanding AI Agents and Agentic AI Definition of AI agents, differences between chatbots, AI assistants, automation and agents, goals and task decomposition, planning and reasoning at a conceptual level, tool use and external integrations, m
• Module 8: How AI Agents Work in Practice Agent instructions and objectives, task planning and subtask generation, selecting and using approved tools, retrieving information from documents and knowledge sources, maintaining task context, checking intermedi
• Module 9: Building No-Code AI Workflows and Agent Prototypes Mapping repetitive tasks, identifying triggers and actions, designing human-in-the-loop workflows, using no-code automation concepts, connecting AI assistants with approved documents and applica
• Module 10: AI for Business Functions and Professional Services AI for administration and office productivity, AI in human resources and recruitment support, AI in marketing and customer engagement, AI for project management and reporting, AI for finance a
• Module 11: Responsible AI, Privacy and Information Security Personal and confidential information, safe handling of organizational documents, data protection principles, access permissions and information classification, bias and fairness, hallucinations
• Module 12: Evaluating, Testing and Improving AI Outputs Accuracy, relevance and completeness, source-grounded verification, checking calculations and factual claims, consistency across repeated tasks, measuring output quality, testing prompts and workflow
• Module 13: Implementing Generative AI and AI Agents in Organizations Identifying organizational readiness, prioritizing high-value use cases, selecting suitable tools, stakeholder engagement, governance and accountability, data access and integration requ

General notes

• The workshop emphasizes practical applications rather than programming. Participants work through realistic scenarios, assess AI-generated outputs, identify limitations, protect sensitive information and develop an actionable plan for applying AI within their professional roles or organizations.
• Business Professionals, Business Owners, Entrepreneurs, Managers, Team Leaders, Administrative Officers, Human Resource Professionals, Marketing Professionals, Communications Officers, Educators, Teachers, Trainers, Researchers, Consultants, University Students, College Students, ICT Professionals, IT Support Officers, Software Developers, Data Analysts, Project Managers, Operations Managers, Customer Service Professionals, Government Officers, NGO Professionals, Digital Transformation Officers, Innovation Managers, and Beginners in Artificial Intelligence.
• ChatGPT, Microsoft Copilot, Google Gemini, Claude, Perplexity, NotebookLM, Microsoft Excel, Microsoft PowerPoint, Canva AI, Power Automate, Zapier, Make, and selected no-code agent-building platforms. Tool availability, features, integrations and subscription requirements vary. Participants should use organization-approved accounts and non-sensitive sample data during practical exercises.
• Practical workshop activities and outputs: A generative AI and AI agents concept map, a reusable prompt library for common workplace tasks, an AI-assisted research summary with source-verification notes, a document-analysis and executive-briefing package, an AI-supported spreadsheet analysis and management summary, an AI agent workflow diagram showing goals, tools, steps and approval points, a no-code AI workflow prototype or detailed design, a responsible AI risk-assessment checklist, an AI output evaluation scorecard, a prioritized organizational AI use-case register, a practical 30–60–90-day AI adoption roadmap.

Frequently asked questions

Schedule & fees