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
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.
At a Glance: Course + Exam Overview
Program Name
AI+ Program Director – Practitioner™
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Duration
- Instructor-Led: 5 days (live or virtual)
- Self-Paced: 40 hours of content
Prerequisites
A good understanding of AI/ML fundamentals, project management experience, business strategy knowledge, familiarity with governance and compliance, and strong leadership and change management skills are essential for this course.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience
Job Roles & Industry Outlook
Sales Specialist
Leverage AI tools to improve lead scoring, sales forecasting, and customer engagement.
Digital Marketing Specialist
Design and execute AI-powered marketing campaigns that personalize customer journeys, optimize targeting, and maximize ROI.
Business Intelligence Analyst
Transform data into actionable insights by applying AI-driven analytics to guide smarter business decisions.
Customer Experience Strategist
Harness AI to personalize customer journeys, automate support, and create seamless experiences that drive loyalty.
Business Analyst
Analyze business processes and ensure AI initiatives comply with legal, ethical, and regulatory standards.
Data Science & AI Specialist
Turn complex datasets into actionable insights by applying AI and machine learning models to solve business challenges.
Industry Growth: AI+ Program Director – Practitioner™
- Leadership in AI Initiatives: Gain the skills to lead AI projects, ensuring alignment with business goals and successful project execution from start to finish.
- Strategic AI Integration: Learn how to seamlessly integrate AI solutions into existing systems, driving innovation and improving operational efficiency across departments.
- Optimized Program Management: Develop expertise in managing resources, timelines, and cross-functional teams to deliver AI projects on time and within budget.
- Enhanced Decision-Making: Equip yourself with the ability to make data-driven, AI-informed decisions that drive business growth and competitive advantage.
- Future-Proof Your Career: Prepare for leadership roles in AI by mastering program management skills that are critical for navigating the rapidly evolving AI landscape.
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.
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
- A good understanding of AI/ML fundamentals, project management experience, business strategy knowledge, familiarity with governance and compliance, and strong leadership and change management skills are essential for this course.
Exam Details
Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via AI proctored exam platform (flexible scheduling)
Exam Blueprint
- Module 1: Foundations of AI for Program Strategy – Introduction - 8%
- Module 2: Identifying AI Opportunities & Use Cases - 8%
- Module 3: Governance & Ethics in AI - 8%
- Module 4: AI Project Lifecycle & Integration - 8%
- Module 5: Data Strategy & Infrastructure for AI - 8%
- Module 6: AI Integration — Build vs Buy vs Partner - 8%
- Module 7: AI Risk Management & Compliance - 8%
- Module 8: AI Tools & Techniques for Project Management - 8%
- Module 9: Leadership in AI - 9%
- Module 10: Scaling AI Initiatives - 9%
- Module 11: Future Trends in AI - 9%
- Module 12: Capstone Project & Presentation - 9%
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
- Access for Tablet & Phone
Frequently Asked Questions
The course includes a mix of theoretical knowledge and practical applications, culminating in an interactive capstone project. This structure ensures that participants gain both conceptual understanding and hands-on experience.
This course is ideal for developers, IT professionals, and anyone with a foundational understanding of AI and cloud computing who wants to enhance their skills in integrating AI with cloud platforms like AWS, Azure, or Google Cloud.
Participants will learn to develop, deploy, and manage AI models on leading cloud platforms. Skills include optimizing AI model performance, ensuring security, meeting compliance standards, and applying AI and cloud concepts to solve real-world problems.
This certification enhances your professional profile by demonstrating proficiency in integrating AI with cloud computing. It equips you with in-demand skills, giving you a competitive edge in the job market and opening doors to lucrative career opportunities.
The certification includes an interactive capstone project where participants apply their knowledge to design and implement AI solutions within cloud environments. This project is designed to simulate real-world scenarios and challenges.