AI for Project Managers and Scrum Masters

AI for Project Managers and Scrum Masters

Instructor: AI CERTs Team

Access provided by Vietnam National University - Hanoi

8 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

8 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

AI-Powered Planning: Use AI tools for sprint planning, backlog prioritization, and resource allocation to enhance forecasting accuracy and delivery.
Workflow Automation Reporting: Automate repetitive tasks like status updates, documentation, and reporting to keep teams focused on high-value work.
Data-Driven Decision Making: Apply AI analytics to interpret project metrics and support faster, evidence-based decisions throughout delivery.
Risk & Responsible AI: Use intelligent tools to identify bottlenecks and delays early, while applying ethical AI practices across Agile projects.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

8 assignments

Taught in English

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There are 8 modules in this course

AI for Project Managers and Scrum Masters is a practical course designed to help professionals integrate AI tools into Agile workflows to drive smarter planning, faster delivery, and data-informed decision-making. As organizations accelerate their adoption of AI-powered project management, practitioners who can effectively lead AI-enhanced Agile teams are becoming indispensable across industries.

In this course, you’ll explore the core principles of AI in Agile environments, including how intelligent tools support sprint planning, backlog prioritization, risk forecasting, and team performance tracking. You’ll learn how to apply automation to routine project tasks and use data-driven insights to guide stakeholder communication, resource management, and delivery outcomes. Through guided exercises and hands-on projects, you’ll gain practical experience with industry tools including ChatGPT, Microsoft Copilot, Jira, Trello AI, ClickUp, Notion AI, Power BI, Tableau Public, Python, Pandas, and workflow automation platforms like Zapier. You’ll also explore predictive analytics, NLP-based collaboration tools, and responsible AI practices specifically tailored to Agile project management environments. By the end of the course, you’ll be able to lead AI-augmented Agile teams, automate complex workflows, and apply intelligent insights to create measurable operational value for projects and organizations across industries.

Introduces the core concepts of Artificial Intelligence (AI) and its role in modern Agile project management. This module explores AI fundamentals, key AI technologies, and how AI can enhance Agile practices such as planning, collaboration, decision-making, automation, and continuous improvement.

What's included

5 videos1 assignment

Builds essential data literacy skills required for Agile project managers to effectively work with AI-driven tools and insights. This module covers data concepts, data quality, analytics fundamentals, visualization, and interpreting data to support evidence-based project decisions.

What's included

10 videos1 assignment

10 videosTotal 39 minutes

2.1 Integrating Big Data in Agile Workflows for Enhanced Predictive Analysis5 minutes
2.2 Advanced Techniques for Big Data Integration5 minutes
2.3 Big Data Integration in a Sprint Forecasting Workflow4 minutes
2.4 Big Data Techniques and Agile Applications4 minutes
2.5 Exploring AI-Driven Decision Models: Theory and Core Concepts5 minutes
2.6 Types of AI-Driven Decision Models4 minutes
2.7 Step-by-Step Workflow for AI Decision Model Integration2 minutes
2.8 AI Models and Their Functions2 minutes
2.9 Case Study: AI-Driven Sprint Timeline Optimization at Amazon Marketplace4 minutes
2.10 Simulation Exercise: AI-Driven Sprint Prediction4 minutes

1 assignmentTotal 30 minutes

Quiz: 230 minutes

Explores how AI can optimize resource allocation, team collaboration, and workforce management in Agile environments. Learners will understand AI applications for capacity planning, skill matching, workload balancing, productivity analysis, and improving team performance.

What's included

7 videos1 assignment

7 videosTotal 33 minutes

3.1 Machine Learning in Predictive Resource Management5 minutes
3.2 Applying ML in Projects6 minutes
3.3 Foundations of AI-Driven Agile Metrics and Core Concepts5 minutes
3.4 Implementing AI to Track and Predict Agile Metrics5 minutes
3.5 Simulation Exercise: AI-Assisted Resource Forecasting Dashboard 3 minutes
3.6 Use-case: AI-Driven Predictive Resource Analytics to Reduce Delivery Delays 4 minutes
3.7 Case Study: AI-Driven Predictive Resource Management for Agile Release Planning5 minutes

1 assignmentTotal 30 minutes

Quiz: 330 minutes

Introduces predictive analytics techniques that help Agile project managers forecast outcomes and manage uncertainty. This module covers AI-driven forecasting, risk prediction, delivery estimates, sprint performance analysis, and using predictive insights to improve project planning and execution.

What's included

7 videos1 assignment

7 videosTotal 30 minutes

4.1 Deep Learning for Predictive Modelling4 minutes
4.2 Common Deep Learning Model Choices5 minutes
4.3 Deep Learning Sprint Risk Prediction: Practical Insights for Project Managers5 minutes
4.4 AI in Risk Management: Understanding Data Patterns, Indicators, Models, and Scoring4 minutes
4.5 Proactive Project Management: Using AI to Predict Delays and Shortages5 minutes
4.6 Case Study: Predicting and Preventing Agile Project Delays Using Deep Learning in a Global Fintech Startup3 minutes
4.7 Simulation Exercise - Management Resource Shortage Forecasting4 minutes

1 assignmentTotal 30 minutes

Quiz: 430 minutes

Examines how AI-powered tools enhance project tracking, reporting, and performance management. Learners will explore automated dashboards, real-time project insights, progress monitoring, anomaly detection, and AI-assisted reporting to improve transparency and stakeholder communication.

What's included

7 videos1 assignment

7 videosTotal 27 minutes

5.1 Real-Time Monitoring with AI 4 minutes
5.2 Detailed Steps: How AI Tools Perform Ongoing Monitoring?4 minutes
5.3 AI-Enhanced Reporting 4 minutes
5.4 How AI Automates Advanced Agile Reports (Step-by-Step)?4 minutes
5.5 Hands-On Simulation Exercise: AI-Driven Agile Sprint Monitoring and Team Health Dashboard 4 minutes
5.6 Use-case: AI-Driven Sprint Monitoring and Workload Optimization in a Large E-Commerce Platform3 minutes
5.7 Case Study: Using AI-Driven Real-Time Monitoring to Detect and Prevent Team Burnout in Agile Delivery 3 minutes

1 assignmentTotal 30 minutes

Quiz: 530 minutes

Focuses on responsible AI adoption within Agile project environments. This module covers ethical AI principles, algorithmic bias, data privacy, security, compliance requirements, transparency, and governance practices for using AI responsibly in project management.

What's included

5 videos1 assignment

5 videosTotal 22 minutes

6.1 Advanced Ethical Considerations: Decision-Making Transparency 6 minutes
6.2 Unintended Consequences of AI Predictions and Ethical Leadership4 minutes
6.3 Regulatory Compliance in Agile AI5 minutes
6.4 Case Study: Mitigating AI Bias in Global Healthcare Resource Allocation5 minutes
6.5 Simulation Exercise -Ethical AI Decision-Making for Agile Resource Allocation Using Ethical AI Analysis Dashboard2 minutes

1 assignmentTotal 30 minutes

Quiz: 630 minutes

Provides guidance on selecting, assessing, and integrating AI tools into Agile workflows. This module covers evaluating AI solutions, understanding business requirements, managing implementation challenges, ensuring user adoption, and measuring the effectiveness of AI-enabled project practices.

What's included

6 videos1 assignment

6 videosTotal 26 minutes

7.1 Evaluating Return on Investment (ROI) in Agile AI Tools5 minutes
7.2 Measuring Effectiveness and Evaluating Adaptability4 minutes
7.3 Change Management Strategies for AI in Agile6 minutes
7.4 Simulation Exercise: Evaluating AI Project Management Tools Using an Interactive Lovable Dashboard3 minutes
7.5 Use Case: AI-Powered Agile Risk Prediction for Digital Banking Transformation3 minutes
7.6 Case Study: AI-Automated Reporting and Risk Forecasting in Agile Consulting5 minutes

1 assignmentTotal 30 minutes

Quiz: 730 minutes

Explores emerging AI trends and their potential impact on the future of Agile project management. This module discusses advancements in AI automation, intelligent project assistants, autonomous workflows, evolving Agile practices, and strategies for preparing organizations for AI-driven transformation.

What's included

6 videos1 assignment

6 videosTotal 27 minutes

8.1 The Future of Autonomous Project Management6 minutes
8.2 AI in Remote and Distributed Agile Teams6 minutes
8.3 Case Study - Autonomous AI in Project Management4 minutes
8.4 Simulation Exercise: AI-Driven Collaboration Optimization for Remote Agile Teams using Dashboard2 minutes
8.5 AI-Enhanced Agile and Its Future4 minutes
Module 08: Course Summary 4 minutes