ARTIFICIAL INTELLIGENCE (AI) PRINCIPLES AND PRACTICES
“Harnessing AI for Strategic Decision-Making, Innovation, and Operational Efficiency”
Course Schedule
| Date | Venue | Fees (Face-to-Face) |
|---|---|---|
| 12 – 16 Oct 2025 | Manama – Bahrain | USD 3495 per delegate |
Course Introduction
Artificial Intelligence is transforming how businesses operate, compete, and deliver value. From automation and prediction to customer experience and strategic insights, AI applications are now central to innovation and growth. However, success depends on more than just algorithms—it requires understanding AI principles, selecting appropriate tools, and managing ethical and operational challenges.
This intensive 5-day course provides a practical, end-to-end understanding of AI. Participants will explore AI fundamentals, real-world applications, model types, and deployment strategies. It emphasizes non-technical and technical perspectives, bridging the gap between business objectives and AI implementation in the enterprise.
Course Objectives
By the end of this course, participants will be able to:
• Understand core AI concepts, methods, and model types
• Identify high-impact use cases and AI opportunities within their domain
• Navigate key steps in the AI project lifecycle—from data preparation to deployment
• Evaluate tools and platforms for AI development and automation
• Address ethical, privacy, and governance concerns in AI adoption
Key Benefits of Attending
• Gain a comprehensive foundation in AI technologies and practices
• Learn how to translate business problems into AI solutions
• Improve decision-making using AI-powered insights and predictions
• Bridge communication between business leaders and technical teams
• Build confidence to support or lead AI initiatives across departments
Intended Audience
This program is designed for:
• Managers, Analysts, and Decision-Makers in any sector
• Digital Transformation and Innovation Leads
• IT and Data Strategy Professionals
• Consultants, Developers, and Technical Professionals new to AI
• Policy Makers and Risk Managers interested in AI ethics and governance
Individual Benefits
Key competencies that will be developed include:
• AI terminology and lifecycle knowledge
• Capability to identify and design data-driven use cases
• Familiarity with AI tools, workflows, and platforms
• Understanding of responsible AI practices and regulatory context
• Strategic thinking around AI impact and change management
Organization Benefits
Upon completing the training course, participants will demonstrate:
• Improved readiness to adopt and scale AI initiatives
• Better collaboration between business and data science teams
• Stronger data governance and risk management around AI systems
• Enhanced customer experience and operational efficiency through AI
• Support for digital transformation and innovation goals
Instructional Methdology
The course follows a blended learning approach combining theory with practice:
• Strategy Briefings – AI foundations, business applications, and deployment frameworks
• Case Studies – Cross-industry use cases and implementation lessons
• Workshops – Use case design, algorithm selection, and project simulation
• Peer Exchange – Industry challenges and success stories
• Tools – Templates for use case evaluation, model planning, and ethical assessment
Course Outline
DETAILED 5-DAY COURSE OUTLINE
Training Hours: 07:30 AM – 03:30 PM
Daily Format: 3–4 Learning Modules | Coffee breaks: 09:30 & 11:15 | Lunch Buffet: 01:00 – 02:00
Day 1: Foundations of AI and Intelligent Systems
Module 1: Understanding Artificial Intelligence (07:30 – 09:30)
• What AI is and isn’t—definitions, history, myths
• Overview of AI subfields: ML, NLP, computer vision, robotics
Module 2: Data as the Core of AI (09:45 – 11:15)
• Data types, quality, and labeling
• Data pipelines and challenges in real-world applications
Module 3: Types of AI Models and Algorithms (11:30 – 01:00)
• Supervised, unsupervised, and reinforcement learning
• Common algorithms and their use cases
Module 4: Workshop – AI Identification Exercise (02:00 – 03:30)
• Mapping AI types to business functions
Day 2: AI Applications and Use Case Development
Module 5: AI in Business Functions (07:30 – 09:30)
• Marketing, finance, supply chain, HR, operations, and customer service
Module 6: Developing AI Use Cases (09:45 – 11:15)
• Problem framing, feasibility, ROI estimation
• Tools for prioritizing use cases
Module 7: AI in Everyday Tools (11:30 – 01:00)
• Chatbots, recommendation engines, document automation, and analytics
Module 8: Workshop – Use Case Canvas (02:00 – 03:30)
• Hands-on exercise building a use case and success criteria
Day 3: AI Tools, Platforms, and Project Lifecycle
Module 9: AI Project Lifecycle (07:30 – 09:30)
• Data preparation, training, evaluation, deployment, monitoring
Module 10: Overview of AI Platforms and Tools (09:45 – 11:15)
• Azure ML, Google Vertex AI, AWS Sagemaker, IBM Watson
• No-code/low-code platforms for non-developers
Module 11: Model Performance and Evaluation (11:30 – 01:00)
• Accuracy, precision, recall, F1-score, confusion matrix
Module 12: Workshop – Lifecycle Mapping (02:00 – 03:30)
• Simulating a basic AI implementation plan
Day 4: Ethics, Governance, and Risk in AI
Module 13: Responsible AI and Bias Management (07:30 – 09:30)
• AI fairness, transparency, accountability, and explainability
Module 14: Legal and Regulatory Landscape (09:45 – 11:15)
• GDPR, AI Act (EU), ISO/IEC AI standards
Module 15: AI Risk and Governance Frameworks (11:30 – 01:00)
• Model risk management, auditability, and control frameworks
Module 16: Workshop – AI Ethics Case Study (02:00 – 03:30)
• Scenario analysis and decision discussion
Day 5: Implementation Strategies and Future Trends
Module 17: Building an AI Roadmap (07:30 – 09:30)
• Skills, systems, and culture required to adopt AI
Module 18: Change Management for AI Projects (09:45 – 11:15)
• Managing expectations, resistance, and cross-functional alignment
Module 19: AI Trends and Innovations (11:30 – 01:00)
• Generative AI, autonomous agents, AI + IoT, and synthetic data
Module 20: Final Review, Action Plans & Certification (02:00 – 03:30)
• Capstone summary, personal AI strategy roadmap, and feedback
Certification
Participants will receive a Certificate of Completion in Artificial Intelligence (AI) Principles and Practices, validating their understanding of AI fundamentals, applications, ethics, and implementation strategies across organizational functions.