AI+ Project Management Practitioner

EDU Trainings s.r.o.

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Obsah kurzu

Module 1: Project Management Overview

1.1 Introduction to Project Management
1.2 Project Management Lifecycle
1.3 Advanced Project Management Tasks
1.4 Project Management Frameworks
1.5 Project Manager’s Roles and Responsibilities

Module 2: Introduction to AI and ML

2.1 Introduction to Artificial Intelligence (AI)
2.2 Introduction to Machine Learning (ML)
2.3 Neural Networks
2.4 AI and ML Applications and Trends
2.5 Case Studies on AI and ML Projects

Module 3: Data Driven Decision Making

3.1 The Importance of Data in Artificial Intelligence
3.2 Data Analysis Techniques
3.4 Applying Data Insights to Project Decisions
3.5 Tools for Data Visualization and Reporting
3.6 Challenges and Best Practices

Module 4: AI-Driven Project Risk Management

4.1 AI in Risk Management – An Introduction
4.2 AI for Risk Mitigation and Response
4.3 AI for Financial and Resource Risk Management
4.4 AI in Risk Management: The Future Scope
4.5 Case Study – AI-based Project Risk Management

Module 5: Planning Project Work Breakdown and Structuring and Project Scheduling by AI

5.1 Introduction to Work Breakdown Structure (WBS)
5.2 AI for WBS Creation
5.3 AI in Project Scheduling
5.4 AI for Resource-Constrained Scheduling
5.5 Case Studies: AI-based WBS and AI Algorithms for Project Scheduling

Module 6: Effective Project Budgeting Using AI

6.1 Introduction to AI in Budgeting
6.2 AI for Estimating Costs and Budget Allocation
6.3 AI for Budget Optimization
6.4 Future of AI in Project Budgeting
6.5 Case  Study:  AI  Algorithms  for  Project  Scheduling, AI- Based Model for Estimating Costs and Budget Allocation

Module 7: AI for Planning Human Resources

7.1 Introduction to AI in Human Resource Planning
7.2 AI for Workforce Allocation
7.3 AI in Skill Matching and Employee Performance Analysis
7.4 The Future of AI in Human Resource Planning
7.5 Case Studies: Designing AI-Based Models for HR Planning

Module 8: Stakeholder Management Using AI

8.1 Introduction to Stakeholder Management and AI
8.2 Identifying and Categorizing Stakeholders Using AI
8.3 Stakeholder Conflicts Management with AI
8.4 Ethics and Future Prospects in AI-based Stakeholder Management
8.5 Case Studies: AI Tools for Stakeholder Management

Module 9: AI-based Project Monitoring

9.1 Introduction to Project Monitoring and AI
9.2 AI-based Tools for Monitoring Project Progress
9.3 AI for Risk Monitoring
9.4 Case Studies: AI Tools for Project Monitoring

Module 10: Transformative Role of Project Management

10.1 Current State of AI in Project Management
10.2 Ethical Considerations in AI-Based Project Management
10.3 Technical Challenges in AI Integration

Additional Module: AI Agents for Project Management Practitioner

1. Understanding AI Agents
2. How Does an AI Agent Work
3. Applications and Trends of AI Agents in Project Management
4. Core Characteristics of AI Agents
5. Significance of AI Agents in Project Management
6. Types of AI Agents
7. Case Study-AI Agents for Agile Project Delivery – Atlassian in Action
8. Hands-On Activity

Cieľová skupina

Aspiring Project Managers: Individuals looking to build a strong foundation in project management while gaining exposure to AI-enabled workflows.
Early-Career Project Professionals: Project coordinators, analysts, or junior PMs seeking to enhance planning, tracking, and reporting using AI tools.
Business and Technical Professionals: Professionals involved in project execution who want to understand how AI can support timelines, resources, and risk awareness.
Team Leads and Supervisors: Leaders responsible for overseeing projects who want better visibility and decision support through AI-assisted insights.
Professionals Transitioning into AI-Supported Roles: Individuals aiming to stay relevant as project environments increasingly adopt AI-driven tools and data-supported execution.

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