AI+ Program Director – Practitioner™

Course code: AP110001

Price of the certification exam is included in the price of the course.

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.
Akční cena
350 EUR

424 EUR including VAT

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Course dates

Starting date: Upon request

Type: Self-paced

Course duration: 40 hours

Language: en

Price without VAT: 350 EUR Akční cena

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Course description

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.

  • 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

Target group

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.

Course structure

Module 1: Foundations of AI for Program Strategy – Introduction

  1. 1.1 Understanding of AI, ML, and Deep Learning
  2. 1.2 AI Lifecycle & Real-World Applications
  3. 1.3 Societal Impact of AI
  4. 1.4 Use Case: Triage System (AI for Emergency Services)
  5. 1.5 Case Study: Retail Recommendation System (Personalizing Customer Experience)
  6. 1.6 Hands-on: Use Teachable Machine to Build a Simple AI Classifier

Module 2: Identifying AI Opportunities & Use Cases

  1. 2.1 Introduce AI Strategy Alignment Frameworks: AI Canvas, Value vs Feasibility Matrix
  2. 2.2 Signs That a Process May Benefit from AI: Repetitive Tasks, Data-Rich Environments, Personalization Needs
  3. 2.3 Prioritization Techniques: Weighted Scoring, Risk-Adjusted ROI
  4. 2.4 Use-Case: Financial AI – Fraud Detection Systems Using AI
  5. 2.5 Case Study: AI-Driven Project Management System for a Program Director
  6. 2.6 Hands-on: Use Trello to Create a Board and Prioritize AI Opportunities Within a Given Scenario

Module 3: Governance & Ethics in AI

  1. 3.1 Responsible AI Principles
  2. 3.2 AI Bias & Risk Mitigation
  3. 3.3 Use-case: Auditing Bias in AI-Powered Recruitment to Ensure Fair Hiring
  4. 3.4 Case Study: Mitigating Algorithmic Bias in Credit Scoring Models to Ensure Fair Lending Practices
  5. 3.5 Hands-on: Use Google’s What-If Tool in Google Colab to Evaluate Model Fairness and Bias

Module 4: AI Project Lifecycle & Integration

  1. 4.1 AI Project Planning & CRISP-DM
  2. 4.2 Integration: Build vs Buy vs Partner
  3. 4.3 AI Project Management Tools
  4. 4.4 Use Cases: AI for Predictive Maintenance (Asset Management in Manufacturing)
  5. 4.5 Tool-Based Hands-on Activity: Simulate an AI Project in Asana

Module 5: Data Strategy & Infrastructure for AI

  1. 5.1 Data Governance & Quality
  2. 5.2 Setting up Data Pipelines for AI
  3. 5.3 Sensitive Data Management
  4. 5.4 Use Case: Retail Inventory System — AI-driven Restocking and Demand Prediction
  5. 5.5 Case Study: Healthcare Data Security — Managing Patient Privacy in AI-Based Healthcare Systems
  6. 5.6 Tool-Based Hands-on Activity: Set up Airbyte Cloud and Build a Basic Data Pipeline

Module 6: AI Integration — Build vs Buy vs Partner

  1. 6.1 Evaluating AI Solutions
  2. 6.2 Vendor Evaluation & Management
  3. 6.3 Use Case: AI Vendor Selection — Choosing Predictive Maintenance Solutions for a Manufacturing Plant
  4. 6.4 Tool-Based Hands-on Activity: Use a Vendor Selection Template to Evaluate AI Vendors (Google Sheets)

Module 7: AI Risk Management & Compliance

  1. 7.1 Regulatory Frameworks
  2. 7.2 Bias Detection & Mitigation
  3. 7.3 Use Case: Facial Recognition Bias (Law Enforcement Systems)
  4. 7.4 Case Study: AI in Finance: Ensuring Compliance in AI Deployments
  5. 7.5 Tool-Based Hands-on Activity: Bias Testing & Fairness Evaluation Using KNIME and Google PAIR Facets Fairness Explorer

Module 8: AI Tools & Techniques for Project Management

  1. 8.1 AI Project Management Tools
  2. 8.2 Data Management Tools
  3. 8.3 Case Study and Use Case: AI Workflow Management: Using project management tools for AI deployment in the retail sector
  4. 8.4 Tool-Based Hands-on Activity: Use Asana to simulate project timelines, setting up tasks and milestones for an AI initiative

Module 9: Leadership in AI

  1. 9.1 Leading AI Teams & Change Management
  2. 9.2 Managing Stakeholders & Communication
  3. 9.3 Use Case: AI in Manufacturing: Leading AI Implementation in a Large-Scale Manufacturing Operation
  4. 9.4 Tool-Based Hands-on Activity: Use Miro to Map Stakeholder Communication Strategies and Identify Key Influencers

Module 10: Scaling AI Initiatives

  1. 10.1 From Pilot to Full-Scale Deployment
  2. 10.2 Organizational Maturity Models for AI
  3. 10.3 Use Case: Scaling AI in Retail: Expanding AI-driven Recommendations Globally
  4. 10.4 Tool-Based Hands-on Activity: Create a Scaling Roadmap Using Lucidchart Outlining Key steps in Scaling AI Initiatives.

Module 11: Future Trends in AI

  1. 11.1 Emerging AI Technologies
  2. 11.2 Use Case / Case Study: AI in Autonomous Vehicles: The future of AI in self-driving cars
  3. 11.3 Tool-Based Hands-on Activity: Explore Hugging Face Transformers for NLP and TensorFlow for Deep Learning Applications

Module 12: Capstone Project & Presentation

  1. 12.1 Capstone Project Overview
  2. 12.2 Presentation & Feedback
  3. 12.3 Final Review & Certification – Method, Process, and Feedback Mechanism

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.

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Certification

50 questions, 70% passing, 90 minutes, online proctored exam

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