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AI CERTS® certification

AI+ Program Director Practitioner™

Master AI Leadership with Practical Program Management

Enquire about this certificationCourse code: AP 110001
AI+ Program Director Practitioner™ certification badge

Course overview

Review the course before deciding whether it is suitable.

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.

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
Exam format
50 questions, 70% passing, 90 minutes, online proctored exam
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.

Course focus

Why this certification may be relevant.

01

Leadership in AI Initiatives:

Gain the skills to lead AI projects, ensuring alignment with business goals and successful project execution from start to finish.

02

Strategic AI Integration:

Learn how to seamlessly integrate AI solutions into existing systems, driving innovation and improving operational efficiency across departments.

03

Optimized Program Management:

Develop expertise in managing resources, timelines, and cross-functional teams to deliver AI projects on time and within budget.

04

Enhanced Decision-Making:

Equip yourself with the ability to make data-driven, AI-informed decisions that drive business growth and competitive advantage.

05

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 it may suit

Check the intended audience against your experience and goals.

Course content

Modules supplied by AI CERTs.

Open each module to review the stated topics.

01Module 1: Foundations of AI for Program Strategy – Introduction
  • 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
02Module 2: Identifying AI Opportunities & Use Cases
  • 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
03Module 3: Governance & Ethics in AI
  • 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
04Module 4: AI Project Lifecycle & Integration
  • 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
05Module 5: Data Strategy & Infrastructure for AI
  • 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
06Module 6: AI Integration — Build vs Buy vs Partner
  • 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)
07Module 7: AI Risk Management & Compliance
  • 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
08Module 8: AI Tools & Techniques for Project Management
  • 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
09Module 9: Leadership in AI
  • 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
10Module 10: Scaling AI Initiatives
  • 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.
11Module 11: Future Trends in AI
  • 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
12Module 12: Capstone Project & Presentation
  • 12.1 Capstone Project Overview
  • 12.2 Presentation & Feedback
  • 12.3 Final Review & Certification – Method, Process, and Feedback Mechanism

Tools referenced by AI CERTs

Platforms and tools included in the course information.

Microsoft ProjectJIRATrelloAsanaMonday.comBasecampWrikeClickUpGitLabConfluenceSmartsheetSlackPower BITableauAzure DevOpsAWS CloudFormationGoogle Cloud AI PlatformTIBCO JaspersoftRapidMinerMinitabBalsamiqMiroZoomJenkinsSalesforceLucidchartServiceNowRedmineAirtableWorkfrontNotionQlikViewKlipfolioHootsuite
Before you enrol

This course information is supplied through the AI CERTs catalogue. Kiwi Fern Education will confirm current availability, delivery arrangements, inclusions and fees before enrolment. The programme is not presented as a New Zealand Qualifications Authority qualification.

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