Estimate Agile Work with Story Points
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Estimate Agile Work with Story Points
This course is part of Agile Project Coordination Specialization
Instructor: LearningMate
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What you'll learn
Learners will apply story points to improve agile estimation, create realistic sprint plans, and forecast project delivery with confidence.
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There are 3 modules in this course
Ready to move beyond flawed, time-based estimates? This beginner-level course, Estimate Agile Work with Story Points, is for any professional on an agile team who wants to build confidence in project planning. You will learn to replace stressful, hour-based guesses with story pointsβa collaborative, relative measure of effort that captures complexity and uncertainty.
Through expert-led videos, real-world case studies from companies like ING Bank, and hands-on practice, you will master the art of relative estimation. You will learn to articulate the value of story points to stakeholders, record them in tools like Jira and Asana, and use your teamβs historical data (velocity) to create sprint plans you can actually deliver. By the end of this course, you will have the skills to drive more accurate, predictable, and collaborative planning in any agile environment.
In this foundational module, learners explore the core principles of agile estimation and discover why modern teams favor story points over traditional time-based estimates. Through a mix of instructional videos, readings, and interactive dialogues, learners will deconstruct the three components of a story point: complexity, effort, and uncertainty. The module focuses on building a strong conceptual understanding, enabling learners to define story points, differentiate them from hour-based estimates, and articulate their value in improving forecasting and collaboration.
What's included
2 videos1 reading2 assignments
2 videosβ’Total 11 minutes
- Why We Use Story Points, Not Hoursβ’6 minutes
- Articulating Story Points Effectivelyβ’5 minutes
1 readingβ’Total 4 minutes
- Story Points vs. Hours: A Foundational Shiftβ’4 minutes
2 assignmentsβ’Total 20 minutes
- Hands On Learning (HOL): Draft Your Pitchβ’10 minutes
- Knowledge Check: Core Conceptsβ’10 minutes
This module bridges theory and practice by demonstrating how to apply story points within real-world agile workflows and project management tools. Learners will gain a hands-on understanding of how to locate, record, and interpret story point data on popular platforms like Jira and Asana. Through practical screencasts and guided simulations, the module demonstrates how this data supports key agile ceremonies, such as backlog refinement and sprint planning, thereby building learner confidence in using these tools to foster transparency and create realistic plans.
What's included
2 videos1 reading1 assignment
2 videosβ’Total 10 minutes
- Why Your Tool is Your Team's Memoryβ’4 minutes
- How to decide on Story Points in Sprint Planningβ’6 minutes
1 readingβ’Total 4 minutes
- The Role of Story Points in Sprint Planningβ’4 minutes
1 assignmentβ’Total 10 minutes
- Knowledge Check: Tools and Processesβ’10 minutes
In the final module, learners will synthesize their knowledge by applying estimation techniques in a collaborative context. They will learn how to participate in estimation activities like Planning Poker and understand the concept of team velocity. The focus shifts from individual estimation to forecasting a team's capacity for future sprints. Through a guided dialogue and a final hands-on project, learners will practice using historical data (velocity) to build a realistic sprint plan, demonstrating their ability to use story points for effective project forecasting and delivery.
What's included
1 video2 readings2 assignments
1 videoβ’Total 5 minutes
- Why Forecasting Matters: From Guessing to Knowingβ’5 minutes
2 readingsβ’Total 7 minutes
- Agile Estimation Techniques and Velocity in Practiceβ’4 minutes
- How to Forecast with Velocityβ’3 minutes
2 assignmentsβ’Total 40 minutes
- Final Project: Agile Estimation in Practiceβ’30 minutes
- Knowledge Check: Estimation and Forecastingβ’10 minutes
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