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.
Product Analytics and AI
Product Analytics and AI
This course is part of multiple programs.
Instructor: Alex Cowan
34,766 already enrolled
Gain insight into a topic and learn the fundamentals.
4.7
(478 reviews)
Beginner level
No prior experience required
Flexible schedule
Approx. 15 hours
Learn at your own pace
93%
Most learners liked this course
What you'll 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'll gain
Details to know
Shareable certificate
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Assessments
14 assignments
Taught in English
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There are 4 modules in this course
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.
What's included
12 videos1 reading2 assignments3 discussion prompts
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.
What's included
14 videos4 assignments1 discussion prompt
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.
What's included
15 videos4 assignments1 peer review2 discussion prompts
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.
What's included
18 videos4 assignments2 discussion prompts
Instructor
Instructor ratings
4.7 (122 ratings)Offered by
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Learner reviews
4.7
478 reviews
- 5 stars
81.41%
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12.10%
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3.96%
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1.67%
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Showing 3 of 478
DW
5
Reviewed on Aug 18, 2020
At the beginning I though it was going to be really difficult, but Alex makes the course fun, dynamic and easy to understand! Thank you!
KG
5
Reviewed on Dec 2, 2020
Excelent ! linking agile to data science in an easy very understandable way from which we can dig further in a solid foundation.
WR
4
Reviewed on Feb 14, 2021
I didn't get as much out of this as the other courses, but I already work with a lot of analytics so the material wasn't really new to me. The interviews with industry professionals were good.
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