Basic Terminology in Artificial Intelligence: AI vs. AGI - Modern AI Techniques . The Machine Intelligence Continuum: Systems That Act - Systems That Predict - Systems That Learn - Systems That Create - Systems That Relate - Systems That Master – Systems that Evolve. The Promises of Artificial Intelligence – The Challenges of Artificial Intelligence – Designing Safe and Ethical AI.

Build an AI-Ready Culture : Be Honest About Your Readiness - Choose the Right Champions - Build An Enterprise-Wide Case For AI - Why You Need a Multi-Disciplinary “AI SWAT Team” - Get Organizational Buy-In - Educate Your Stakeholders Plan Your Implementation : Rank Business Goals - Perform Opportunity Analysis - AI Strategy Framework - Know Your Data and Analytics - Technical Prerequisites - Build vs. Buy - Calculate ROI and Allocate Budget - Pick the Right “True North” Metric

Build Machine Learning Models : AI Is Not a Silver Bullet - Assessing the Performance of Your Models - Common Mistakes With Machine Learning Models - Machine Learning Workflow - Maintain an Experimental Mindset. Experiment And Iterate : Agile Development - Technical Debt - Deployment and Scaling - Iteration and Improvement.

Obstacles And Opportunities : Current Obstacles - What AI Can Do for Enterprise Functions . General And Administrative : Finance and Accounting - Legal and Compliance - Records Maintenance - General Operations. Business Intelligence And Analytics : Data Wrangling - Data Architecture - Analytics . Software Development.

Marketing : Digital Ad Optimization - Recommendations and Personalization. Sales : Customer Segmentation - Lead Qualification and Scoring - Sales Development - Sales Analytics. Customer Support : Conversational Agents - Social Listening - Customer Churn - Lifetime Value . The Ethics Of Enterprise AI.