14 Topics
10 Days
Programme Overview
Training Description
Who Should Attend
This course is ideal for;
1. Project Managers
2. Program Managers
3. Agile Coaches
4. Business Analysts
5. Product Managers
6. Team Leads
7. Technology Consultants
8. Innovation Managers
9. Digital Transformation Leaders
10. Anyone interested in the future of project management
Session Objectives
- Understand the core concepts of generative AI
- Learn to use generative AI for project ideation and planning
- Master the art of prompt engineering for project tasks
- Automate documentation and reporting with AI
- Enhance stakeholder communication and engagement
- Use generative AI to analyze project data and identify patterns
- Understand the ethical and security considerations of AI
- Develop a strategy for integrating AI into existing workflows
- Create a framework for measuring the ROI of AI in projects
- Position yourself as a leader in AI-driven project management
About the Course
The emergence of generative AI is poised to fundamentally alter how projects are conceived, planned, and executed. This "Driving Innovation: Generative AI for Project Managers Training Course" is a forward-thinking program designed to equip project managers with the knowledge and practical skills needed to harness the power of this transformative technology. You will learn to integrate generative AI tools into your workflows to automate tasks, enhance creativity, and drive unprecedented levels of productivity and efficiency.
This intensive 10-day program will explore the core concepts behind large language models and other generative AI systems, moving beyond a basic understanding to strategic application. From automating documentation and stakeholder communication to generating project plans and analyzing complex data, this course will provide a comprehensive roadmap for leveraging generative AI to your advantage. By the end of this program, you will be prepared to lead with a new, powerful set of tools, positioning yourself as a visionary leader at the forefront of project management innovation.
Curriculum & Topics
14 Topics | 10 Days
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Subtopic 1.1:
What is generative AI and how does it work?
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Subtopic 1.2:
The difference between traditional AI and generative AI
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Subtopic 1.3:
An overview of large language models (LLMs) and their applications
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Subtopic 1.4:
Key concepts like transformers and neural networks
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Subtopic 1.5:
The impact of generative AI on project management
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Subtopic 2.1:
Using AI to brainstorm project ideas and requirements
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Subtopic 2.2:
Generating initial project charters and scope statements
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Subtopic 2.3:
Automating the creation of work breakdown structures (WBS)
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Subtopic 2.4:
Leveraging AI for resource and timeline estimation
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Subtopic 2.5:
Creating a dynamic and adaptable project plan
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Subtopic 3.1:
The fundamentals of effective prompt writing
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Subtopic 3.2:
Techniques for generating high-quality project outputs
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Subtopic 3.3:
Using prompts to refine and iterate on plans
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Subtopic 3.4:
Customizing AI outputs for specific project needs
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Subtopic 3.5:
The role of prompt engineering in daily PM tasks
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Subtopic 4.1:
Using AI to draft project proposals and reports
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Subtopic 4.2:
Generating status updates and meeting summaries
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Subtopic 4.3:
Creating and organizing project documentation
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Subtopic 4.4:
Automating the creation of risk registers and issue logs
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Subtopic 4.5:
The future of documentation in an AI-powered world
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Subtopic 5.1:
Using AI to draft clear and concise emails
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Subtopic 5.2:
Generating presentations and reports for stakeholders
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Subtopic 5.3:
Summarizing long documents and conversations
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Subtopic 5.4:
Personalizing communication based on stakeholder needs
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Subtopic 5.5:
The role of AI in improving team collaboration
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Subtopic 6.1:
Using AI to analyze project data for potential risks
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Subtopic 6.2:
Generating what-if scenarios and contingency plans
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Subtopic 6.3:
Creating risk mitigation strategies
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Subtopic 6.4:
The importance of a proactive approach to risk
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Subtopic 6.5:
The role of AI in decision-making
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Subtopic 7.1:
Understanding the data that powers generative AI
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Subtopic 7.2:
The importance of data privacy and security
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Subtopic 7.3:
The concept of data bias and how it impacts project outputs
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Subtopic 7.4:
The role of a PM in data governance
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Subtopic 7.5:
Ethical considerations of using sensitive data
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Subtopic 8.1:
An overview of popular generative AI tools (e.g., GPT, Bard)
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Subtopic 8.2:
The role of open-source models in project management
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Subtopic 8.3:
Integrating AI tools into existing software stacks
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Subtopic 8.4:
The future of the AI tool ecosystem
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Subtopic 8.5:
Choosing the right tools for your specific project needs
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Subtopic 9.1:
The intersection of Agile methodologies and generative AI
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Subtopic 9.2:
Using AI to enhance sprint planning and backlog refinement
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Subtopic 9.3:
Automating retrospectives and feedback loops
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Subtopic 9.4:
The role of AI in continuous improvement
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Subtopic 9.5:
The future of AI-powered Agile teams
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Subtopic 10.1:
Using AI to generate innovative solutions to project challenges
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Subtopic 10.2:
Brainstorming with AI to overcome roadblocks
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Subtopic 10.3:
The role of AI as a creative partner
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Subtopic 10.4:
Leveraging AI for ideation sessions
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Subtopic 10.5:
The future of human-AI collaboration
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Subtopic 11.1:
Defining success metrics for AI integration
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Subtopic 11.2:
Measuring productivity and efficiency gains
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Subtopic 11.3:
Calculating the ROI of using AI in projects
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Subtopic 11.4:
The importance of a data-driven approach to evaluation
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Subtopic 11.5:
The long-term impact on project performance
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Subtopic 12.1:
Understanding the ethical guidelines for AI use
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Subtopic 12.2:
Data security and intellectual property concerns
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Subtopic 12.3:
The importance of transparency and accountability
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Subtopic 12.4:
The risk of misinformation and hallucinations
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Subtopic 12.5:
Building a responsible AI framework
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Subtopic 13.1:
Creating a strategy for AI adoption
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Subtopic 13.2:
The role of a PM in driving change
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Subtopic 13.3:
Overcoming resistance to new technology
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Subtopic 13.4:
Training and upskilling your team
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Subtopic 13.5:
Building a roadmap for enterprise-wide integration
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Subtopic 14.1:
Analyzing real-world examples of AI in project management
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Subtopic 14.2:
Hands-on exercises using generative AI tools
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Subtopic 14.3:
Developing a project plan for an AI-powered initiative
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Subtopic 14.4:
Presenting your findings to peers
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Subtopic 14.5:
Peer-to-peer feedback and discussion
