About this programme

This course provides a comprehensive introduction to the field of Artificial Intelligence (AI). It covers the fundamental concepts, techniques, and applications of AI, equipping learners with the knowledge required to understand and engage with AI systems. The course explores the history of AI, core areas like machine learning, natural language processing, and robotics, and examines ethical considerations surrounding AI technology. Through theoretical lessons and practical exercises, participants will gain a solid foundation in AI and its real-world applications.

Course Duration

5 Days

Who Should Attend

Business leaders and managers exploring AI adoption
IT and data professionals seeking AI foundational knowledge
Project managers involved in AI projects
Entrepreneurs and innovators interested in AI solutions

Learning outcomes

What you'll walk away with

By the end of this course, participants will be able to:

Understand the key concepts and history of Artificial Intelligence.
Identify the main areas and techniques of AI, including machine learning, neural networks, and natural language processing.
Apply basic AI techniques to solve simple problems.
Recognize the ethical and societal implications of AI.
Explore current and future trends in AI development and deployment.

Course modules

What we cover, module by module

Module 1: Introduction to AI

History and evolution of AI
Key concepts: machine learning, deep learning, NLP
AI applications overview
Case Study: AI transforming customer service in a retail company
Practical Exercise: Identify AI opportunities in participants’ organizations

Module 2: AI Techniques and Approaches

Supervised, unsupervised, and reinforcement learning
Neural networks and deep learning basics
Case Study: Fraud detection using machine learning
Practical Exercise: Build a simple classification model

Module 3: AI Tools and Platforms

Overview of popular AI frameworks (TensorFlow, PyTorch, Scikit-learn)
AI integration into business processes
Case Study: Predictive analytics in finance
Practical Exercise: Hands-on experiment with an AI tool

Module 4: AI Ethics and Governance

AI bias, fairness, and accountability
Data privacy and ethical considerations
Case Study: Ethical dilemmas in facial recognition
Practical Exercise: Assess ethical risks in an AI project

Module 5: Future of AI and Strategic Implementation

Emerging trends and technologies
AI adoption strategy and roadmap development
Case Study: AI-powered supply chain optimization
Practical Exercise: Draft an AI implementation plan for your organization

Impact

Where the change lands

Organizational Impact:

Identify AI-driven opportunities to improve efficiency
Make data-driven decisions leveraging AI insights
Enhance competitiveness through AI adoption

Individual Impact:

Gain foundational AI knowledge and technical awareness
Develop skills to evaluate AI tools and applications
Understand ethical and governance considerations

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