Introduction

In the era of big data, AI-powered decision support systems are transforming how organizations make informed decisions. This comprehensive 5-day course is designed to equip professionals with the skills and knowledge to develop, implement, and manage decision support systems that leverage artificial intelligence. Participants will explore the components, technologies, and methodologies that underpin these systems and learn how to apply them across various business domains.

• Understand the fundamental concepts of AI-powered decision support systems.
• Identify and evaluate the different components and architectures of these systems.
• Gain expertise in the tools and technologies used to build decision support systems.
• Learn how to implement AI-driven decision support in business settings.
• Explore ethical considerations and best practices for deploying AI systems.

Course Outlines

Day 1: Introduction to AI-Powered Decision Support Systems

• Overview of Decision Support Systems (DSS)
• The role of AI in transforming DSS
• Key components of AI-driven DSS
• Introduction to machine learning and data analytics
• Case studies of AI-powered DSS in various industries

Day 2: System Architecture and Components

• Understanding AI architectures for decision support
• Data management and integration
• Model selection and evaluation
• User interface design for DSS
• Scalability and performance considerations

Day 3: Tools and Technologies

• Overview of AI and machine learning tools
• Introduction to data visualization tools
• Exploring cloud platforms for AI deployment
• Hands-on session with popular AI frameworks
• Integrating AI tools into existing DSS

Day 4: Implementing AI in Business

• Identifying business challenges and opportunities
• Developing an AI strategy for decision support
• Managing AI project lifecycles
• Change management and user adoption
• Measuring the impact of AI-powered DSS

Day 5: Ethics, Challenges, and Future Trends

• Ethical considerations in AI decision-making
• Addressing biases and ensuring fairness
• Overcoming technical and organizational challenges
• Trends and innovations in AI-powered DSS
• Preparing for the future of AI in decision support