AI+ Program Director – Practitioner™
AP 110001
Master AI Leadership with Practical Program Management- AI Strategy Development: Learn to design and implement AI strategies that align with business goals, driving innovation and performance.
- Leading AI Projects: Gain skills in managing AI projects, ensuring timely execution, resource allocation, and effective collaboration.
- AI Program Integration: Understand how to integrate AI into business processes for seamless transitions and maximum value.
- Managing AI Teams: Lead cross-functional teams, fostering collaboration and driving continuous improvement in AI initiatives.
- Future-Proofing AI Programs: Stay ahead of AI trends and adapt strategies to ensure long-term competitiveness in the evolving landscape.
Why This Certification Matters
At a Glance: Course + Exam Overview
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
Who Should Enroll?
AI Project Managers: Ideal for project managers looking to lead AI initiatives and ensure successful implementation across organizations.
Business Leaders: For executives and managers aiming to integrate AI into business strategies and drive operational efficiency.
Program Directors: Designed for program directors who want to master AI project management and lead cross-functional AI teams.
AI Professionals: For AI specialists seeking to enhance their leadership skills and move into strategic program management roles.
Change Managers: Great for professionals managing organizational change and looking to implement AI-driven transformation effectively.
Job Roles & Industry Outlook
AI Program Manager
Lead AI projects, ensuring alignment with organizational goals, managing timelines, and optimizing resources for successful AI program delivery.
AI Integration Specialist
Oversee the integration of AI solutions into existing systems, optimizing processes and ensuring smooth adoption across departments.
AI Strategy Consultant
Advise organizations on AI strategies, helping them align AI initiatives with business objectives to drive innovation and enhance efficiency.
AI Transformation Leader
Guide organizations through the AI adoption process, managing change and ensuring successful transformation using AI-powered solutions.
AI Portfolio Manager
Manage a portfolio of AI projects, balancing resources, timelines, and risks to ensure the successful execution and scaling of AI initiatives across the business.
Skills You’ll Gain
- AI Strategy Development for Programs
- AI Project Management
- AI System Integration
- Cross-Functional Leadership
- AI Governance and Compliance
- Risk Management in AI Projects
- AI Change Management
- Performance Measurement and Evaluation
What You'll Learn
- 1.1 Understanding of AI, ML, and Deep Learning
- 1.2 AI Lifecycle & Real-World Applications
- 1.3 Societal Impact of AI
- 1.4 Use Case: Triage System (AI for Emergency Services)
- 1.5 Case Study: Retail Recommendation System (Personalizing Customer Experience)
- 1.6 Hands-on: Use Teachable Machine to Build a Simple AI Classifier
- 2.1 Introduce AI Strategy Alignment Frameworks: AI Canvas, Value vs Feasibility Matrix
- 2.2 Signs That a Process May Benefit from AI: Repetitive Tasks, Data-Rich Environments, Personalization Needs
- 2.3 Prioritization Techniques: Weighted Scoring, Risk-Adjusted ROI
- 2.4 Use-Case: Financial AI – Fraud Detection Systems Using AI
- 2.5 Case Study: AI-Driven Project Management System for a Program Director
- 2.6 Hands-on: Use Trello to Create a Board and Prioritize AI Opportunities Within a Given Scenario
- 3.1 Responsible AI Principles
- 3.2 AI Bias & Risk Mitigation
- 3.3 Use-case: Auditing Bias in AI-Powered Recruitment to Ensure Fair Hiring
- 3.4 Case Study: Mitigating Algorithmic Bias in Credit Scoring Models to Ensure Fair Lending Practices
- 3.5 Hands-on: Use Google’s What-If Tool in Google Colab to Evaluate Model Fairness and Bias
- 4.1 AI Project Planning & CRISP-DM
- 4.2 Integration: Build vs Buy vs Partner
- 4.3 AI Project Management Tools
- 4.4 Use Cases: AI for Predictive Maintenance (Asset Management in Manufacturing)
- 4.5 Tool-Based Hands-on Activity: Simulate an AI Project in Asana
- 5.1 Data Governance & Quality
- 5.2 Setting up Data Pipelines for AI
- 5.3 Sensitive Data Management
- 5.4 Use Case: Retail Inventory System — AI-driven Restocking and Demand Prediction
- 5.5 Case Study: Healthcare Data Security — Managing Patient Privacy in AI-Based Healthcare Systems
- 5.6 Tool-Based Hands-on Activity: Set up Airbyte Cloud and Build a Basic Data Pipeline
- 6.1 Evaluating AI Solutions
- 6.2 Vendor Evaluation & Management
- 6.3 Use Case: AI Vendor Selection — Choosing Predictive Maintenance Solutions for a Manufacturing Plant
- 6.4 Tool-Based Hands-on Activity: Use a Vendor Selection Template to Evaluate AI Vendors (Google Sheets)
- 7.1 Regulatory Frameworks
- 7.2 Bias Detection & Mitigation
- 7.3 Use Case: Facial Recognition Bias (Law Enforcement Systems)
- 7.4 Case Study: AI in Finance: Ensuring Compliance in AI Deployments
- 7.5 Tool-Based Hands-on Activity: Bias Testing & Fairness Evaluation Using KNIME and Google PAIR Facets Fairness Explorer
- 8.1 AI Project Management Tools
- 8.2 Data Management Tools
- 8.3 Case Study and Use Case: AI Workflow Management: Using project management tools for AI deployment in the retail sector
- 8.4 Tool-Based Hands-on Activity: Use Asana to simulate project timelines, setting up tasks and milestones for an AI initiative
- 9.1 Leading AI Teams & Change Management
- 9.2 Managing Stakeholders & Communication
- 9.3 Use Case: AI in Manufacturing: Leading AI Implementation in a Large-Scale Manufacturing Operation
- 9.4 Tool-Based Hands-on Activity: Use Miro to Map Stakeholder Communication Strategies and Identify Key Influencers
- 10.1 From Pilot to Full-Scale Deployment
- 10.2 Organizational Maturity Models for AI
- 10.3 Use Case: Scaling AI in Retail: Expanding AI-driven Recommendations Globally
- 10.4 Tool-Based Hands-on Activity: Create a Scaling Roadmap Using Lucidchart Outlining Key steps in Scaling AI Initiatives.
- 11.1 Emerging AI Technologies
- 11.2 Use Case / Case Study: AI in Autonomous Vehicles: The future of AI in self-driving cars
- 11.3 Tool-Based Hands-on Activity: Explore Hugging Face Transformers for NLP and TensorFlow for Deep Learning Applications
- 12.1 Capstone Project Overview
- 12.2 Presentation & Feedback
- 12.3 Final Review & Certification – Method, Process, and Feedback Mechanism
Tools You'll Explore
Microsoft Project
JIRA
Trello
Asana
Monday.com
Basecamp
Wrike
ClickUp
GitLab
Confluence
Smartsheet
Slack
Power BI
Tableau
Azure DevOps
AWS CloudFormation
Google Cloud AI Platform
TIBCO Jaspersoft
RapidMiner
Minitab
Balsamiq
Miro
Zoom
Jenkins
Salesforce
Lucidchart
ServiceNow
Redmine
Airtable
Workfront
Notion
QlikView
Klipfolio
Hootsuite
Prerequisites
- AI Fundamentals: Basic AI/ML concepts and terminology familiarity.
- Project Management: Experience managing projects, timelines, and stakeholders.
- Business Strategy: Understanding of business strategy and KPI-driven decision-making.
- Governance & Compliance: Working knowledge of data privacy, risk, and compliance.
- Leadership & Change: Comfort with cross-functional leadership and change management.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via proctored exam platform (flexible scheduling)
Exam Blueprint:
- Foundations of AI for Program Strategy – Introduction - 5%
- Identifying AI Opportunities & Use Cases – 9%
- Governance & Ethics in AI – 9%
- AI Project Lifecycle & Integration – 9%
- Data Strategy & Infrastructure for AI – 9%
- AI Integration: Build vs Buy vs Partner – 9%
- AI Risk Management & Compliance – 9%
- AI Tools & Techniques for Project Management – 9%
- Leadership in AI – 8%
- Scaling AI Initiatives – 8%
- Future Trends in AI – 8%
- Capstone Project & Presentation – 8%
Choose the Format That Fits Your Schedule
What’s Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
Instructor-Led (Live Virtual/Classroom)
- 5 days of intensive training with live demos
- Real-time Q&A, peer collaboration, and hands-on labs
- Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
- ~40 hours of on-demand video lessons, e-book, podcasts, and interactive labs
- Learn anywhere, anytime, with modular quizzes to track progress
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Get CertifiedFrequently Asked Questions
Yes, you’ll gain practical experience in managing AI projects, leading teams, and executing AI strategies, allowing you to apply these skills to real-world AI initiatives right away.
The AI + Program Director Practitioner course is tailored to developing leadership and management skills for AI projects, focusing on strategic planning, team coordination, and effective communication with stakeholders, rather than just the technical aspects of AI.
You’ll work on projects like creating AI strategies, managing project lifecycles, leading teams, and implementing AI governance, ensuring AI initiatives align with business goals.
The course blends leadership concepts with practical AI management through case studies, simulations, and hands-on exercises, helping you lead AI projects effectively.
This course prepares you for roles like AI Program Director or AI Project Manager, equipping you with the skills to lead AI initiatives and manage AI projects across industries.
