AI for Project Managers - Topic-wise Course Structure

1. AI Foundations for Project Managers

- Understanding AI, ML, NLP, and Generative AI
- Types of AI (Predictive, Prescriptive, Generative)
- The role of AI in business and project environments
- Ethical use of AI in decision-making

2. Evolving Role of the Project Manager

- How AI is reshaping project management responsibilities
- Skills of the future PM: strategic thinking, AI fluency, data intuition
- Case studies: AI-led vs. traditional project management

3. AI Use Cases Across the Project Lifecycle

- Project Planning: AI-powered scheduling and resource estimation
- Risk Management: Predictive analytics and risk modeling
- Communication & Collaboration: AI-based assistants, summarization
- Execution & Monitoring: Real-time dashboards, auto-updates
- Post-Implementation Reviews: Sentiment analysis, impact mapping

4. Hands-On with AI Tools

- Overview & demos of ClickUp AI, Notion AI, Fireflies.ai, Fellow.app, Motion, ChatGPT, Jasper AI
- Tool-based use case walkthroughs
- Practice: Automating meeting notes, building schedules, email drafts

5. AI-Augmented Decision Making

- How to leverage AI-generated insights
- Using LLMs for project stakeholder management
- Confidence scoring and risk flagging through AI
- Bias, interpretability, and PM's judgment in AI-enabled decisions

6. Generative AI in Agile & Hybrid Environments

- Prompt engineering for Agile ceremonies
- Automating user stories, backlogs, retrospectives, and AI for Project Managers
- AI-driven sprint planning and daily stand-ups
- Scaling Agile with AI in large teams

7. Data & Privacy Concerns in Project AI

- AI compliance: GDPR, CCPA, ISO 42001
- Responsible data usage in projects
- Bias, fairness, transparency, explainability
- AI Governance and documentation best practices

8. Strategy, Implementation & Change Management

- Building an AI adoption roadmap
- Cost-benefit frameworks & ROI justification
- Stakeholder buy-in & team reskilling
- Managing resistance to AI in project environments

9. Capstone Project & Presentation

- Build an AI-augmented project plan
- Use tools to demonstrate automation and insights.
- Peer review and expert feedback
- Final Q&A and course wrap-up