Few capabilities focus agile like a strong analytics program. Such a program determines where a team should focus from one agile iteration (sprint) to the next. Successful analytics are rarely hard to understand and are often startling in their clarity. In this course, developed at the Darden School of Business at the University of Virginia, you'll learn how to build a strong analytics infrastructure for your team, integrating it with the core of your drive to value.
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About this Course
What you will learn
How to naturally, habitually tie your team’s work to actionable analytics that help you drive to user value.
How to pair your hypotheses on customer personas and problem with analytics.
How to test propositions (a la Lean Startup) so you don’t build features no one wants.
How to instrument actionable observation into everything you build (a la Lean UX).
Skills you will gain
- Software Development
- Product Management
- Agile Software Development
Offered by

University of Virginia
A premier institution of higher education, The University of Virginia offers outstanding academics, world-class faculty, and an inspiring, supportive environment. Founded by Thomas Jefferson in 1819, the University is guided by his vision of discovery, innovation, and development of the full potential of students from all walks of life. Through these courses, global learners have an opportunity to study with renowned scholars and thought leaders.
Syllabus - What you will learn from this course
Introduction and Customer Analytics
Without an actionable view of who your customer is and what problems/jobs/habits they have, you’re operating on a shaky foundation. This week, we’ll look at how to pair your qualitative analytics on customer hypotheses with testable analytics.
Demand Analytics
Why build something no one wants? It seems like an obvious question, yet a lot (probably >50%) of software ends up lightly used or not used at all. This week, we’ll look at how to run fast but definitive experiments to test demand.
UX Analytics
Strong usability most often comes from ongoing diligence as opposed to big redesigns. Teams that do the hard work of consistently testing usability are rewarded with a consistent stream of customer wins and a culture of experimentation that makes work more enjoyable and rewarding.
Analytics and Data Science
The availability of big data and the ascendance of machine learning can supercharge the way you approach analytics. This week, we're going to learn how data science is changing analytics and how you can create a focused, productive interfaces to a data science capability.
Reviews
- 5 stars81.95%
- 4 stars12.37%
- 3 stars4.12%
- 2 stars1.28%
- 1 star0.25%
TOP REVIEWS FROM AGILE ANALYTICS
Great perspectives on mapping analytics to product innovation pipeline. Learnt a lot and enjoyed it.
Another fantastic course from Alex Cowan! Insightful, timely and shares great perspective from experts
This was a really good course for demonstrating how you can apply analytics, not just a run through of the theory. Really good.
I loved the whole specialization has a lot of benefits about product management from A to Z yet some lessons were confusing and doesn't have a clear view of how to use a specific concept or tool.
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