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Generative AI Essentials Training Course

The Generative AI Essentials Training Course is a comprehensive professional development program designed to provide executives, managers, specialists, and business professionals with a practical understanding of…

AIG · Generative AIAll LevelsClassroomEnglish , Arabic
Duration
5 Days
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Course Overview

The Generative AI Essentials Training Course is a comprehensive professional development program designed to provide executives, managers, specialists, and business professionals with a practical understanding of Generative Artificial Intelligence (Generative AI) and its rapidly expanding role in modern organizations. As Generative AI transforms how organizations create content, automate knowledge work, improve customer engagement, accelerate innovation, and enhance productivity, professionals across every industry require a solid foundation in its capabilities, limitations, governance, and business applications. This course introduces participants to the core concepts of Generative AI while emphasizing practical implementation in enterprise environments. Government entities, ministries, public sector organizations, banks and financial institutions, oil and gas companies, healthcare providers, manufacturers, educational institutions, consulting firms, and multinational corporations are increasingly adopting Generative AI to improve operational efficiency, streamline business processes, support decision-making, enhance communication, develop digital services, automate documentation, strengthen knowledge management, and deliver personalized customer experiences. Understanding how to responsibly apply Generative AI has become an essential competency for organizations pursuing digital transformation, operational excellence, and sustainable innovation. Throughout this course, participants will explore the principles of Generative AI, including Large Language Models (LLMs), foundation models, prompt engineering, AI-powered assistants, multimodal AI, AI-generated text, images, audio, and business content creation. The program also covers enterprise use cases, AI governance, responsible AI, data privacy, cybersecurity, intellectual property considerations, AI risk management, implementation strategies, organizational readiness, and performance evaluation. Practical demonstrations, case studies, and interactive workshops enable participants to understand how Generative AI can deliver measurable business value across multiple industries. The Generative AI Essentials Training Course combines strategic insight with practical application to help organizations confidently adopt Generative AI technologies. By the end of the program, participants will understand how to identify valuable use cases, develop effective AI workflows, apply prompt engineering techniques, evaluate AI-generated outputs, establish governance practices, and support enterprise-wide adoption of Generative AI that improves productivity, innovation, collaboration, and long-term organizational performance.

Learning Objectives

  • Analyze the principles, capabilities, and limitations of Generative Artificial Intelligence.
  • Develop a practical understanding of Large Language Models and Generative AI technologies.
  • Evaluate business opportunities for implementing Generative AI across organizational functions.
  • Apply prompt engineering techniques to improve AI-generated results.
  • Design practical workflows that integrate Generative AI into business operations.
  • Improve productivity through responsible use of AI-powered tools and assistants.
  • Strengthen understanding of AI governance, ethics, cybersecurity, privacy, and intellectual property.
  • Implement best practices for evaluating and validating AI-generated content.
  • Assess organizational readiness for enterprise Generative AI adoption.
  • Align Generative AI initiatives with digital transformation, innovation, operational excellence, and strategic business objectives.

Who Should Attend

This course is designed for executives, senior managers, department managers, digital transformation leaders, innovation managers, project managers, IT managers, operations managers, business analysts, consultants, communication professionals, knowledge management specialists, learning and development professionals, marketing managers, customer experience leaders, and decision-makers seeking to understand and implement Generative AI within their organizations. The program is equally valuable for professionals working in government entities, ministries, public sector organizations, banks and financial institutions, oil and gas organizations, healthcare providers, manufacturing companies, utility organizations, telecommunications companies, educational institutions, consulting firms, and multinational corporations pursuing AI-enabled transformation. Business professionals involved in strategy, finance, procurement, legal services, human resources, compliance, governance, internal audit, cybersecurity, research, innovation, quality management, customer service, and enterprise transformation will benefit from the practical frameworks and internationally recognized best practices presented throughout the course.

Learning Outcomes

  • By the end of this course, participants will be able to:
  • Explain the core concepts and business value of Generative Artificial Intelligence.
  • Differentiate between Generative AI, traditional AI, and Machine Learning technologies.
  • Apply prompt engineering techniques to produce accurate and effective AI outputs.
  • Identify high-value Generative AI use cases across business functions.
  • Evaluate AI-generated content for quality, accuracy, bias, and reliability.
  • Apply responsible AI principles, governance requirements, and ethical practices.
  • Recognize cybersecurity, privacy, and intellectual property considerations associated with Generative AI.
  • Support organizational adoption of Generative AI technologies using structured implementation approaches.
  • Improve productivity by integrating AI-powered assistants into daily business activities.
  • Contribute to enterprise AI initiatives that enhance innovation, efficiency, and organizational performance.

Course Outline

Course Outline:

Day 1

Foundations of Generative Artificial Intelligence

  • Introduction to Generative AI
  • Evolution of Artificial Intelligence and foundation models
  • Large Language Models (LLMs) and Generative AI technologies
  • Business value and enterprise applications
  • Practical workshop on identifying Generative AI opportunities
Day 2

Generative AI Applications and Prompt Engineering

  • Enterprise applications of Generative AI
  • Prompt engineering principles and techniques
  • AI-powered content creation and knowledge management
  • AI assistants for productivity and decision support
  • Practical exercise on developing effective AI prompts
Day 3

Responsible AI and Enterprise Governance

  • AI governance frameworks
  • Responsible AI principles and ethical considerations
  • Data privacy, cybersecurity, and intellectual property
  • AI risk management and regulatory compliance
  • Workshop on evaluating responsible AI implementation
Day 4

Implementing Generative AI Across the Enterprise

  • Organizational readiness and implementation planning
  • Integrating Generative AI into business workflows
  • Change management and workforce enablement
  • Measuring AI performance and business value
  • Practical workshop on designing a Generative AI implementation roadmap
Day 5

Future of Generative AI and Organizational Transformation

  • Emerging trends in Generative AI
  • Scaling AI across enterprise operations
  • Continuous improvement and AI-driven innovation
  • International best practices for enterprise AI adoption
  • Final workshop involving the development of a comprehensive Generative AI adoption strategy integrating business use cases, prompt engineering, governance, responsible AI principles, cybersecurity, data protection, implementation planning, organizational readiness, performance measurement, change management, and continuous improvement to maximize operational efficiency, digital transformation, innovation, and sustainable organizational success.

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