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- Level Foundation
- Duration 14 hours
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Offered by
About
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.Modules
Welcome!
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1
Readings
1
Readings
- Course Overview & Requirements
Introduction to Product Analytics & AI
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7
Videos
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3
Discussion
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2
Assignment
2
Assignment
- Customer Analytics
- Introduction and Customer Analytics
3
Discussions
- Tools & Tips for Story Mapping
- Focal Points: Trent the Technician
- Looking Forward to Upcoming Topics
7
Videos
- Intentional Iteration
- Science for the Win
- Recap: Hypothesis-Driven Development
- Getting Outside the Building with Trent the Technician
- Describing the Customer Journey for Testability: Trent the Technician
- Focal Point: The User Journey
- Your Analytics Portfolio
Running Experiments for Fun and Profit
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5
Videos
5
Videos
- Designing Actionable Inferences: DV's, IV's, and Causality
- Testing with Retrospective Experiment Patterns
- Testing with Prospective Experiment Patterns
- Understanding Enough about Statistics for Now
- Separating Laggards vs. Innovators: The Two Ways to be Wrong and the Two Ways to be Right
Testing Demand
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5
Videos
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2
Assignment
2
Assignment
- Testing Motivations with MVPs
- Experiments
5
Videos
- Lean Startup and the Demand Hypothesis
- Demand Testing at Enable Quiz
- Designing Experiments
- Experiment Design with MVPs
- Designing User Habits: The Hook Framework
Experiment Patterns
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9
Videos
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1
Discussion
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2
Assignment
2
Assignment
- Testing Features
- Testing Demand and Experiment Patterns
1
Discussions
- Fake Feature Tests & Your Experience
9
Videos
- Five Experiment Charters
- The Fake Feature Test
- Testing Features: Running the Experiment
- Testing Funnels
- Testing Cohorts
- Experiment Design: Testing a Coding Course for Designers & Managers
- Experiment Execution: Testing a Coding Course for Designers & Managers
- Diverging Your Ideas with Generative AI
- Interview: Laura Klein on Practice of Lean UX
From Qualitative Usability Testing to Analytics
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6
Videos
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2
Assignment
2
Assignment
- Testing Analytics
- User Stories & Analytics
6
Videos
- Analytics All the Time
- Qualitative Usability Testing
- The Test You Already Have
- Pairing Your User Stories with Analytics: Trent the Technician
- Getting Outside the Building With Ivan the Inside Salesperson
- Pairing Your User Stories with Analytics: Ivan the Inside Salesperson
Instrumenting Observation for Quantitative Analytics
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9
Videos
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2
Discussion
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1
PeerReview
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2
Assignment
2
Assignment
- A/B Testing
- Qualitative and Quantitative Analytics
1
Peer Review
- Creating a Testable Solution
2
Discussions
- Google Analytics & Alex's Website
- Tools & Tips for A/B Testing
9
Videos
- Analyzing Dependent Variables with Google Analytics
- Google Analytics: The Littlest Overview
- From Design to Code: Trent the Technician
- From Code to Analytics: Trent the Technician
- A/B Testing
- Mapping Analytics: Ivan the Inside Salesperson
- Designing, Coding, and Testing: Ivan the Inside Salesperson
- From Inference to Product Priorities: Four Sprints with HinH
- Pushing Yourself on Comparables with Generative AI
Data Science and AI
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15
Videos
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2
Discussion
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4
Assignment
4
Assignment
- Data Science
- Data Executions
- Data Science IRL
- Analytics and Data Science
2
Discussions
- Data Science & Your Experience
- Tips for Working with a Data Science Team
15
Videos
- What is Data Science?
- Data Science and Generative AI
- Product Jobs-to-be-Done and Your AI Portfolio
- Facilitating Collaboration with Your Data Science Team
- Interview: Drew Conway on Data Science
- Interview: Drew Conway’s Data Science Journey
- Maturing Your Analytics & AI Capability
- Interview: Casey Lichtendahl: Data Science and You
- Interview: Casey Lichtendahl: Closer Look at the Work of Data Science
- Interview: Casey Lichtendahl: Data at Rest vs. Data in Motion
- Generative AI IRL: the Jedburgh App's
- Data Science IRL: Intro to the Casino Jack Case
- Data Science IRL: Data Wrangling and Exploratory Analysis
- Data Science IRL: Testing Hypotheses and Designing Interventions
- Course Close
Auto Summary
Unlock the power of agile methodologies with "Agile Analytics," a foundational course designed to enhance your business management skills through strategic analytics. Created by the prestigious Darden School of Business at the University of Virginia and offered by Coursera, this course focuses on developing a robust analytics program that can guide your team through agile iterations with precision and clarity. Over the span of 840 minutes, you will learn to construct an effective analytics infrastructure that seamlessly integrates with your core business objectives, ensuring that your team remains focused and driven towards value creation. This course is perfect for business professionals and managers seeking to harness the potential of agile analytics to boost team performance and decision-making. Flexible subscription options including Starter, Professional, and Paid plans make it easy to get started and fit the course into your schedule. Join now to transform your approach to agile project management with clear, impactful analytics.