AI+ Program Director Practitioner™ - eLearning (exam included)
448,00 EUR
- 40 hours
Lead Strategic AI Initiatives with Confidence Step into leadership with the AI+ Program Director Practitioner™ certification — a high‑impact program designed for experienced professionals responsible for driving complex, enterprise‑scale AI and digital transformation programs. This course equips you with the strategic frameworks, governance models, and practical tools needed to plan, execute, and oversee AI initiatives that deliver measurable business value. You’ll learn how to align AI programs with organizational goals, manage risk and ethical considerations, lead cross‑functional teams, and ensure robust governance and stakeholder engagement. Through real‑world case studies, hands‑on exercises, and expert insights, you’ll develop the capabilities to steer AI strategy at the highest level and drive sustainable, responsible innovation across your organization. Ideal for program directors, transformation leaders, senior managers, and executives charting the future of AI adoption.
Key Features
Language
Course and material in English
Level
Intermediate level (Category: AI+ Practitioner)
Access
1 year access to the platform 24/7
40 hours of video lessons & multimedia
60 hours of study time recommendation
eBooks, Audiobooks, Podcasts
Quizzes, Assessments, and Course Resources
Exam
Online Proctored Exam with One Free Retake
Certificate
Certification of completion included

Lead AI Programs with Expertise and Impact
Learn to create and execute AI strategies that align with organizational objectives, fostering innovation and measurable performance.

Learning Outcomes
At the end of this course, you will be able to:
AI Program Leadership
Master how to manage AI programs end-to-end, aligning initiatives with business goals and optimizing resource allocation
Leading Cross-Functional Teams
Gain expertise in coordinating technical and non-technical teams to successfully deliver AI-driven projects
AI Integration & Implementation
Learn how to embed AI solutions into existing business systems to streamline workflows and boost efficiency
Risk & Compliance Oversight
Understand how to identify, assess, and mitigate AI project risks while ensuring adherence to privacy, security, and ethical standards.
Performance Measurement & Optimization
Develop skills to track AI program success, enhance performance, and ensure outcomes support strategic objectives.
Tools explored
- Microsoft Project
- Jira, Trello, Asana, Monday.com
- ClickUp
- Basecamp
- Wrike
- GitlAb
- Confluence
- Smartsheet
- Slack
- Power BI
- Tableau
- Azure DevOps
- AWS CloudFormation
- Google Cloud AI Platform
- TIBCO Jaspersoft
- RapidMiner
- Minitab
- Balsamiq
- Miro
- Jenkins
- Salesforce
- Lucidchart
- ServiceNow
- Redmine
- Airtable
- Workfront
- Notion
- QlikView
- Klipfolio
- Hootsuite

Course timeline
Foundations of AI for Program Strategy – Introduction
Lesson 1
- Understanding AI, ML, and Deep Learning
- AI Lifecycle & Real-World Applications
- Societal Impact of AI
- Use Case: AI for Emergency Services Triage System
- Case Study: Retail Recommendation System for Personalized Customer Experience
- Hands-On: Build a Simple AI Classifier with Teachable Machine
Identifying AI Opportunities & Use Cases
Lesson 2
- AI Strategy Alignment Frameworks: AI Canvas, Value vs Feasibility Matrix
- Identifying Processes Suitable for AI: Repetitive Tasks, Data-Rich Environments, Personalization Needs
- Prioritization Techniques: Weighted Scoring, Risk-Adjusted ROI
- Use Case: AI for Fraud Detection in Finance
- Case Study: AI-Driven Project Management System for Program Directors
- Hands-On: Create a Trello Board to Prioritize AI Opportunities
Governance & Ethics in AI
Lesson 3
- Responsible AI Principles
- Mitigating AI Bias & Risk
- Use Case: Auditing Bias in AI Recruitment for Fair Hiring
- Case Study: Mitigating Algorithmic Bias in Credit Scoring Models
- Hands-On: Evaluate Model Fairness Using Google’s What-If Tool in Colab
AI Project Lifecycle & Integration
Lesson 4
- AI Project Planning & CRISP-DM Methodology
- Integration Strategies: Build vs Buy vs Partner
- AI Project Management Tools Overview
- Use Case: Predictive Maintenance in Manufacturing
- Hands-On: Simulate an AI Project in Asana
Data Strategy & Infrastructure for AI
Lesson 5
- Data Governance & Quality Management
- Setting Up Data Pipelines for AI
- Handling Sensitive Data
- Use Case: Retail Inventory — AI-Driven Restocking & Demand Prediction
- Case Study: Healthcare Data Security & Patient Privacy
- Hands-On: Build a Basic Data Pipeline with Airbyte Cloud
AI Integration — Build vs Buy vs Partner
Lesson 6
- Evaluating AI Solutions
- Vendor Evaluation & Management
- Use Case: Selecting AI Predictive Maintenance Vendors
- Hands-On: Evaluate AI Vendors Using a Google Sheets Template
AI Risk Management & Compliance
Lesson 7
- Regulatory Frameworks for AI
- Bias Detection & Mitigation Strategies
- Use Case: Facial Recognition Bias in Law Enforcement
- Case Study: Ensuring Compliance in AI Deployments in Finance
- Hands-On: Bias Testing & Fairness Evaluation with KNIME and Google PAIR Facets
AI Tools & Techniques for Project Management
Lesson 8
- Overview of AI Project Management Tools
- Data Management Tools for AI Projects
- Case Study: AI Workflow Management in Retail Deployment
- Hands-On: Simulate AI Project Timelines, Tasks & Milestones in Asana
Leadership in AI
Lesson 9
- Leading AI Teams & Driving Change
- Stakeholder Management & Communication Strategies
- Use Case: AI Implementation Leadership in Large-Scale Manufacturing
- Hands-On: Map Stakeholder Communication Using Miro
Scaling AI Initiatives
Lesson 10
- Transition from Pilot to Full-Scale Deployment
- Organizational Maturity Models for AI
- Use Case: Scaling AI-Driven Retail Recommendations Globally
- Hands-On: Design a Scaling Roadmap Using Lucidchart
Future Trends in AI
Lesson 11
- Emerging AI Technologies & Applications
- Use Case / Case Study: AI in Autonomous Vehicles
- Hands-On: Explore Hugging Face Transformers for NLP and TensorFlow for Deep Learning
Capstone Project & Presentation
Lesson 12
- Overview of Capstone Project
- Presentation & Feedback Sessions
- Final Review & Certification Process

Who Should Enroll in this Program?
AI Project Managers: Perfect for project managers aiming to lead AI initiatives and drive successful organizational implementation.
Business Leaders & Executives: Ideal for leaders looking to embed AI into business strategies and enhance operational efficiency.
Program Directors: Designed for directors who want to excel in AI program management and oversee cross-functional AI teams.
AI Professionals: Suited for AI specialists seeking to expand into strategic leadership and program management roles.
Change Management Professionals: Beneficial for those guiding organizational change and implementing AI-driven transformations effectively.
More Details
Prerequisites
- AI Basics: Familiarity with core AI and machine learning concepts and terminology.
- Project Management Experience: Background in managing projects, schedules, and stakeholder expectations.
- Business Acumen: Understanding business strategy and making KPI-driven decisions.
- Governance & Compliance Knowledge: Awareness of data privacy, risk management, and regulatory compliance.
- Leadership & Change Management: Experience leading cross-functional teams and driving organizational change.
Exam Details
- Duration: 90 minutes
- Passing :70% (35/50)
- Format: 50 multiple-choice/multiple-response questions
- Delivery Method: Online via proctored exam platform (flexible scheduling)
- Language: English
Licensing and accreditation
This course is offered by AVC according to Partner Program Agreement and complies with the License Agreement requirements.
Equity Policy
AVC does not provide accommodations due to a disability or medical condition of any students. Candidates are encouraged to reach out to AVC for guidance and support throughout the accommodation process.
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