AI+ Program Director – Practitioner™

AI+ Program Director Practitioner™ – Course Outline

Program Overview

The AI+ Program Director Practitioner certification equips leaders with the skills to design, implement, and oversee AI-driven initiatives across organizational functions. This program provides strategic expertise in AI governance, project planning, ethical deployment, and cross-functional coordination. Participants learn to align AI solutions with business goals, manage multidisciplinary teams, and ensure responsible, compliant AI adoption. By mastering both technical foundations and executive-level decision-making, certified professionals can drive innovation, optimize operations, and guide their organizations through successful AI transformation.

Course Objectives

 • Apply program management principles in AI-driven environments
 • Integrate AI tools into program planning, governance, and delivery
 • Use data-driven insights for strategic decision-making
 • Optimize program performance through predictive analytics
 • Manage risks, stakeholders, and resources using AI-enabled approaches

Target Audience

 • Program Directors & Senior Project Managers
 • Portfolio Managers
 • PMO Leaders & Executives
 • Digital Transformation Leaders
 • Strategy & Operations Professionals

Assessment & Certification

 • Knowledge checks and quizzes
 • Practical assignments / case study analysis
 • Final assessment (optional)
 • AI+ Program Director – Practitioner™ Certificate of Completion

Training Methodology

 • Instructor-led training (Classroom / Virtual)

Course Modules

Module 1: Foundations of AI for Program Strategy – Introduction

 • Understanding AI, ML, and Deep Learning
 • AI lifecycle and real-world applications
 • Societal impact of AI
 • Use case: AI triage system for emergency services
 • Case study: Retail recommendation system
 • Hands-on: Build AI classifier using Teachable Machine

Module 2: Identifying AI Opportunities & Use Cases

 • AI strategy frameworks (AI Canvas, Value vs Feasibility Matrix)
 • Identifying AI-suitable processes
 • Prioritization techniques (weighted scoring, risk-adjusted ROI)
 • Use case: AI fraud detection in finance
 • Case study: AI-driven project management system
 • Hands-on: AI opportunity prioritization using Trello

Module 3: Governance & Ethics in AI

 • Responsible AI principles
 • AI bias and risk mitigation
 • Use case: Recruitment bias auditing
 • Case study: Bias in credit scoring systems
 • Hands-on: Fairness evaluation using Google What-If Tool

Module 4: AI Project Lifecycle & Integration

 • AI project planning (CRISP-DM)
 • Build vs buy vs partner decisions
 • AI project management tools
 • Use case: Predictive maintenance in manufacturing
 • Hands-on: AI project simulation in Asana

Module 5: Data Strategy & Infrastructure for AI

 • Data governance and quality
 • AI data pipelines
 • Sensitive data management
 • Use case: AI-driven retail inventory optimization
 • Case study: Healthcare data security in AI systems
 • Hands-on: Build data pipeline using Airbyte Cloud

Module 6: AI Integration — Build vs Buy vs Partner

 • Evaluating AI solutions
 • Vendor assessment and management
 • Use case: Predictive maintenance vendor selection
 • Hands-on: Vendor evaluation using Google Sheets

Module 7: AI Risk Management & Compliance

 • Regulatory frameworks
 • Bias detection and mitigation
 • Use case: Facial recognition bias in law enforcement
 • Case study: AI compliance in finance
 • Hands-on: Bias testing using KNIME and FAIR tools

Module 8: AI Tools & Techniques for Project Management

 • AI project management tools
 • Data management tools
 • Case study: AI workflow management in retail
 • Hands-on: AI project timeline simulation in Asana

Module 9: Leadership in AI

 • Leading AI teams and change management
 • Stakeholder communication strategies
 • Use case: AI leadership in manufacturing
 • Hands-on: Stakeholder mapping using Miro

Module 10: Scaling AI Initiatives

 • Pilot to full-scale deployment
 • AI maturity models
 • Use case: Scaling AI in retail globally
 • Hands-on: AI scaling roadmap using Lucidchart

Module 11: Future Trends in AI

 • Emerging AI technologies
 • Use case: AI in autonomous vehicles
 • Hands-on: Hugging Face and TensorFlow exploration

Module 12: Capstone Project & Presentation

 • Capstone project overview
 • Final presentation and feedback
 • Certification review and evaluation process