About this programme

Generative AI is transforming industries by enabling machines to create text, images, code, designs, and more. This training provides participants with an understanding of how generative AI works, its practical applications, ethical considerations, and hands-on experience with leading tools. Through real-world case studies, participants will learn to harness AI for innovation, problem-solving, and decision-making in their organizations.

Duration

5 Days

Who Should Attend

Business leaders and managers exploring AI-driven innovation
IT professionals, data analysts, and developers interested in AI applications
HR, marketing, finance, and operations professionals leveraging AI in workflows
Educators, researchers, and policy makers working with emerging technologies
Anyone seeking foundational knowledge in generative AI and its business value

Learning outcomes

What you'll walk away with

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

Understand the principles of generative AI and its underlying technologies.
Explore leading tools (e.g., ChatGPT, MidJourney, Stable Diffusion, GitHub Copilot).
Apply generative AI in real-world domains such as content creation, design, analytics, and automation.
Assess risks, ethics, and governance frameworks for responsible AI use.
Develop strategies for integrating generative AI into organizational workflows.

Course modules

What we cover, module by module

Module 1: Foundations of Generative AI

Introduction to AI and machine learning basics
How generative AI models work (LLMs, diffusion models, GANs)
Case Study: Comparing AI-generated vs. human-generated content

Module 2: Tools and Platforms

Exploring text, image, audio, and code generation tools
Integrating APIs and cloud-based AI services
Case Study: Automating customer support with AI assistants

Module 3: Applications in Business and Creativity

Marketing, HR, finance, and operations use cases
Enhancing creativity in design, media, and education
Case Study: Using AI to speed up report generation and analysis

Module 4: Risks, Ethics, and Governance

Bias, misinformation, intellectual property concerns
Privacy, security, and regulatory issues
Case Study: Addressing ethical dilemmas in AI-generated content

Module 5: Building an AI-Ready Strategy

Assessing organizational readiness for AI adoption
Best practices for implementing AI in workflows
Case Study: Developing a generative AI roadmap for an organization

Impact

Where the change lands

Organizational Impact

Improved innovation and productivity through AI-driven solutions
Cost savings and efficiency from automation of creative and analytical tasks
Strengthened competitive edge by integrating AI into products and services
Better preparedness for managing AI adoption, risks, and governance

Individual Impact

Deeper understanding of generative AI concepts and tools
Practical experience applying AI in business, creative, and analytical contexts
Increased confidence in identifying opportunities for AI integration
Enhanced career growth in AI-related fields and digital transformation roles

Dates and locations

Upcoming intakes

Every intake is limited to a small cohort. Booking closes when a date fills or three weeks before the start, whichever comes first.

Full calendar

City	Starts	Ends	Delivery	Book
NakuruNext	20 Jul 2026	24 Jul 2026	In-Person	Book
Kigali	20 Jul 2026	24 Jul 2026	In-Person	Book
Accra	20 Jul 2026	24 Jul 2026	In-Person	Book
Kisumu	27 Jul 2026	31 Jul 2026	In-Person	Book
Johannesburg	27 Jul 2026	31 Jul 2026	In-Person	Book
Dakar	27 Jul 2026	31 Jul 2026	In-Person	Book