Course Overview
TOPEnhance enterprise program leadership through predictive analytics and intelligent automation with the AI+ Program Director Practitioner™ course. The program focuses on AI-driven portfolio prioritization, cross-program dependency management, and proactive risk forecasting across complex initiatives. It highlights how machine learning and scenario modeling support investment decisions, benefits realization, and delivery predictability. Designed for large-scale environments, the course demonstrates how AI enables stronger executive oversight and strategic alignment across programs.
Scheduled Classes
TOP| 07/27/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 08/31/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 09/28/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 10/26/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 11/30/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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| 12/14/26 - NVT - Virtual Classroom - Virtual-Instructor Led | (click to enroll)
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What You'll Learn
TOP- Apply AI-driven analytics to manage portfolios, programs, and interdependencies at scale
- Use predictive models to anticipate program risks, schedule conflicts, and delivery impacts
- Optimize resource allocation and investment prioritization using data-driven insights
- Automate executive reporting, performance dashboards, and benefits tracking
- Integrate AI governance, ethics, and controls into enterprise program leadership decisions
Outline
TOPFoundations of AI for Program Strategy – Introduction
- Understanding of AI, ML, and Deep Learning
- AI Lifecycle & Real-World Applications
- Societal Impact of AI
- Use Case: Triage System (AI for Emergency Services)
- Case Study: Retail Recommendation System (Personalizing Customer Experience)
- Hands-on: Use Teachable Machine to Build a Simple AI Classifier
Identifying AI Opportunities & Use Cases
- Introduce AI Strategy Alignment Frameworks: AI Canvas, Value vs Feasibility Matrix
- Signs That a Process May Benefit from AI: Repetitive Tasks, Data-Rich Environments, Personalization Needs
- Prioritization Techniques: Weighted Scoring, Risk-Adjusted ROI
- Use-Case: Financial AI – Fraud Detection Systems Using AI
- Case Study: AI-Driven Project Management System for a Program Director
- Hands-on: Use Trello to Create a Board and Prioritize AI Opportunities Within a Given Scenario
Governance & Ethics in AI
- Responsible AI Principles
- AI Bias & Risk Mitigation
- Use-case: Auditing Bias in AI-Powered Recruitment to Ensure Fair Hiring
- Case Study: Mitigating Algorithmic Bias in Credit Scoring Models to Ensure Fair Lending Practices
- Hands-on: Use Google’s What-If Tool in Google Colab to Evaluate Model Fairness and Bias
AI Project Lifecycle & Integration
- AI Project Planning & CRISP-DM
- Integration: Build vs Buy vs Partner
- AI Project Management Tools
- Use Cases: AI for Predictive Maintenance (Asset Management in Manufacturing)
- Tool-Based Hands-on Activity: Simulate an AI Project in Asana
Data Strategy & Infrastructure for AI
- Data Governance & Quality
- Setting up Data Pipelines for AI
- Sensitive Data Management
- Use Case: Retail Inventory System — AI-driven Restocking and Demand Prediction
- Case Study: Healthcare Data Security — Managing Patient Privacy in AI-Based Healthcare Systems
- Tool-Based Hands-on Activity: Set up Airbyte Cloud and Build a Basic Data Pipeline
Prerequisites
TOPRequired
- Basic AI/ML concepts and terminology familiarity
- Experience managing projects, timelines, and stakeholders
- Understanding of business strategy and KPI-driven decision-making
- Working knowledge of data privacy, risk, and compliance
- Comfort with cross-functional leadership and change management
