Artificial Intelligence (AI) Essentials for Business

This training course is a suitably wide range of professionals but will significantly benefit: 

• Quality, Safety, Reliability, and Security Officers
• Project Managers
• Executive Managers
• Marketing Managers
• Engineers specializing in instrumentation, process, systems, electrical, and mechanical fields
• Finance Professionals, Budget Planners, Decision-Makers, and Policy-Makers

Day 1:  Understanding AI and Its Business Applications

• What is Artificial Intelligence? Key concepts and business success stories
• Human vs. AI intelligence: Strengths, limitations, and opportunities
• The evolution of AI: From early concepts to modern advancements
• Exploring intelligent agents and their impact on business functions
• The boundaries of AI: What AI can and cannot do
• AI-driven decision-making techniques and their business impact

Day 2: Intelligent Agents and Business Automation

• Fundamentals of intelligent agents: Definition and role in AI systems
• Types of AI agents: Reactive, goal-based, utility-based, and learning agents
• Knowledge bases vs. databases: How AI systems store and process information
• Logical reasoning principles: The foundation of AI decision-making
• Understanding unification and deduction in AI systems

Day 3:   Machine Learning for Business Insights

• Introduction to machine learning: Key concepts and real-world applications
• Supervised vs. unsupervised learning: Understanding different AI learning methods
• Classification and clustering techniques for business intelligence
• Introduction to neural networks: How AI learns from data
• Feature recognition and data analysis for AI-driven decision-making
• Developing machine learning models for business optimization

Day 4:  Fuzzy Logic and AI-Driven Decision Making

• What is fuzzy logic? Understanding uncertainty in AI
• Fuzzy logic vs. probability: When to use each approach
• Fuzzy sets and fuzzy rules: How AI makes complex decisions
• Applications of fuzzy logic in AI-driven business operations
• Developing a simple AI model using fuzzy logic

Day 5: Genetic Algorithms and Business Optimization

• Introduction to genetic algorithms (GA): AI-driven problem-solving
• Why businesses need optimization: Maximization and minimization strategies
• How genetic algorithms work: Selection, mutation, and crossover processes
• AI-driven business process improvement using genetic algorithms
• Real-world applications of genetic algorithms in decision-making
• Implementing AI-driven optimization models for business growth