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.
ofrecido por
Universidad de VirginiaAcerca de este Curso
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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 15 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Chino (simplificado), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Turco (Turkish), Inglés (English), Español (Spanish)
Qué aprenderás
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).
Habilidades que obtendrás
Software DevelopmentProduct ManagementAgile Software Development
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel principiante
Aprox. 15 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Chino (simplificado), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Turco (Turkish), Inglés (English), Español (Spanish)
ofrecido por
Universidad de 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.
Programa - Qué aprenderás en este curso
3 horas para completar
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.
3 horas para completar
13 videos (Total 66 minutos), 2 lecturas, 4 cuestionarios
13 videos
Review: Hypothesis-Driven Development3m
Agile Analytics at HVAC in a Hurry2m
Jobs To Be Done at HVAC in a Hurry5m
Getting Outside the Building With Ivan7m
Focal Point: The User Journey6m
Introducing Enable Quiz1m
Outlining the User Journey7m
Outlining with Pirate Metrics3m
Designing User Habits: The Hook Framework4m
Mapping Analytics: Trent the Technician10m
Mapping Analytics: Ivan the Inside Salesperson6m
Your Analytics Portfolio2m
2 lecturas
Course Overview & Requirements10m
Getting Project Management Institute (PMI) Professional Development Units (PDUs) and Scrum Alliance SEUs10m
4 ejercicios de práctica
User Journeys and Pirate Metrics30m
User Habits and Mapping Analytics30m
Customer Analytics
Introduction and Customer Analytics30m
3 horas para completar
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.
3 horas para completar
12 videos (Total 61 minutos)
12 videos
Testing Motivation with MVPs3m
Designing Experiments4m
Experiment Design with MVPs4m
Five Experiment Charters2m
The Fake Feature Test4m
Testing Features: Running the Experiment3m
Testing Funnels6m
Testing Cohorts7m
Experiment Design: Testing a Coding Course for Designers & Managers4m
Experiment Execution: Testing a Coding Course for Designers & Managers5m
Interview: Laura Klein on Practice of Lean UX10m
4 ejercicios de práctica
Testing Motivations with MVPs30m
Experiments30m
Testing Features
Testing Demand and Experiment Patterns30m
6 horas para completar
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.
6 horas para completar
11 videos (Total 73 minutos)
11 videos
Qualitative Usability Testing9m
The Test You Already Have2m
Pairing Your User Stories with Analytics: Trent the Technician7m
Pairing Your User Stories with Analytics: Ivan the Inside Salesperson10m
Analyzing Dependent Variables with Google Analytics4m
Google Analytics: The Littlest Overview10m
From Design to Code: Trent the Technician4m
From Code to Analytics: Trent the Technician4m
A/B Testing7m
Designing, Coding, and Testing: Ivan the Inside Salesperson6m
4 ejercicios de práctica
Testing Analytics30m
User Stories & Analytics30m
A/B Testing
Qualitative and Quantitative Analytics30m
3 horas para completar
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.
3 horas para completar
12 videos (Total 75 minutos)
12 videos
Facilitating Collaboration with Your Data Science Team4m
Interview: Drew Conway on Data Science8m
Interview: Drew Conway’s Data Science Journey9m
Four Types of Data Executions1m
Interview: Casey Lichtendahl: Data Science and You6m
Interview: Casey Lichtendahl: Closer Look at X, Y, Z10m
Interview: Casey Lichtendahl: Data at Rest vs. Data in Motion6m
Data Science IRL: Intro to the Casino Jack Case8m
Data Science IRL: Data Wrangling and Exploratory Analysis9m
Data Science IRL: Testing Hypotheses and Designing Interventions5m
Course Close1m
4 ejercicios de práctica
Data Science30m
Data Executions30m
Data Science IRL
Analytics and Data Science30m
Reseñas
Principales reseñas sobre AGILE ANALYTICS
por MG2 de ene. de 2021
Very exciting course, probably the most exciting part of the specification so far. Helps to fill in the gaps on the theory front and provided a lot of useful practical advice as well.
por AM12 de dic. de 2020
Gives thoughtfull ideas on how to manage and make use of data in agile development. Absolutely meets the expectations as it is a beginner level course. Highly recommended.
por KM14 de nov. de 2020
Great course to gain knowledge n the subject area specially for the intermediates, i highly recommend this. thank you for the immense support throughout the course.
por ET24 de nov. de 2020
I really appreciated the mixture of video lessons, a lot of quizzes and in particular the several interviews which gave a nice insight into the 'real' world.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
¿Qué recibiré si me suscribo a este Programa especializado?
Is financial aid available?
¿Recibiré crédito universitario por completar el Curso?
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