Become A Data Driven Product Manager

The only course that focuses 100% on data for product managers.
What you'll learn
Product Management
Data analytics
Data Driven Solutions
Define success metrics
A/B test
Read data
Take decisions based on Data
Product Data Driven
User funnel (AARRR) analysis
Conversion rates
Find relevant metrics
Answer interview questions on Data Analytics
Cognitive Biases
Design charts
Present data to stakeholders
Communicate with stakeholders on data
Define events and properties
Requirements
No prior experience is required
Description
Hello and welcome to the course Data Analytics for Product Managers. This course covers all topics you need to know to be a data-driven product manager.In this course, you will learn #1 - How to look at user metrics & business KPIs #2- Look at your data and get insights#3- Take action on your data#4- Track feature success#5- Communicate on data with your stakeholders#6- Use tools like A/B test to drive Data-Driven DecisionsWorking for a software company and having to make decisions on the product can be tricky and complicated. All courses, conferences on product management talk about being data-driven, "take data-driven decisions", "use data to drive decisions..." but articles don't really give a deep understanding of what it means. What should you track? How to look at company KPIs and catch insights? How to act or react to dataHow to work with data departmentsHow to use Data analytic tools like A/B testetc.I was there 6 years ago and I quickly understood that if I want to be a proactive PM who makes data-driven decisions, I need to become an expert in data analytics. For the past year, after feeling confident about it, I decided to gather all my learnings from articles, experiences as a PM and create the most complete course on Data Analytics for Product Managers. My Name is David Kremlinsky. I work for now 6 years in the software industry. Before that, I studied Business Management and completed an MBA in Business Management and Entrepreneurship. I am passionate about data and in this course, I want to turn you into an expert but most importantly, make you enjoy data analytics. What will you learn in this course?Very simple. Be a Data-Driven Product ManagerWhat makes it different from other courses?I thought about the perfect syllabus to cover all topics. To remember something, you have to practice it. In this course, I used real-life examples using the known product as Airbnb, Facebook, Twitter, Amazon, Google, etc, to cover a maximum of industries and make sure the knowledge you acquire doesn't stop to a simple theoretical knowledge. For this purpose, you will practice on a real case. You will use everything you learned during the course to analyze the situation and give your thought.Most important, you need to practice. The last part of this course is a simulation. You will be a PM at Podcasty and together we will go over your first weeks. I want this course to be interactive! So, don't hesitate to send me feedback, contact me if you have any questions!After the course, you will be part of a community! I hope to share with you the best articles on product KPIs, open discussions on data and new courses, videos coming!I wish you good luck!David
Overview
Section 1: Chapter 1 - User Funnel Analysis (Part 1)
Lecture 1 Introduction
Lecture 2 Top of the funnel > Acquisition Metrics
Lecture 3 Activation metrics
Lecture 4 Engagement metrics
Lecture 5 Retention metrics
Lecture 6 Churn metrics
Lecture 7 Revenue metrics
Lecture 8 Vanity/Lagging metrics VS Actionable/ Leading metrics
Section 2: Chapter 2 - User Funnel Analysis (Part 2)
Lecture 9 Metrics by industry
Lecture 10 Monetization metrics
Lecture 11 Define actionable company KPIs
Lecture 12 Practice: Define KPIs
Lecture 13 BONUS: practice interview questions on product KPIs
Lecture 14 Your turn! Analyze user funnel analysis
Section 3: Chapter 3 - Measure Product Success
Lecture 15 Introduction
Lecture 16 Type of KPIs
Lecture 17 Good metric definition
Lecture 18 Define success of your features
Lecture 19 Track performance of your features
Lecture 20 BONUS: interview questions
Section 4: Chapter 4 - Get insights from the data
Lecture 21 Introduction
Lecture 22 Approach the data - Define Correlation
Lecture 23 Approach the data - Correlation VS Causation
Lecture 24 Read the data
Lecture 25 Conversion rates metrics
Lecture 26 Cognitive Biases
Section 5: Chapter 5 - From metrics to product decisions
Lecture 27 Introduction
Lecture 28 Act on Data
Lecture 29 React on data
Lecture 30 Let's practice!
Section 6: Chapter 6 - Track actions in your product
Lecture 31 Introduction
Lecture 32 Prerequisite on Data Infrastructures
Lecture 33 Define your events
Lecture 34 Define your properties
Lecture 35 Common tips on events tracking
Section 7: Chapter 7 - Stakeholder interactions
Lecture 36 Introduction
Lecture 37 Collaboration with data teams
Lecture 38 Present data to other stakeholders
Lecture 39 Design charts
Lecture 40 Common tips for data visualisation
Section 8: Chapter 8 - A/B testing
Lecture 41 Introduction
Lecture 42 Before the A/B test
Lecture 43 A/B testing: define a winner!
Section 9: You just get hired as new PM! Welcome to Podcasty!
Lecture 44 Introduction
Lecture 45 1st day at work! Meeting with the HR
Lecture 46 1st day: Interview with Stakeholders
Lecture 47 2nd day at work - Define new KPIs
Lecture 48 3rd day at work - Find assumptions
Lecture 49 2nd week at work - Assumptions to hypothesis
Lecture 50 3rd week at work - Test your hypothesis!
Lecture 51 AB test results!
Lecture 52 7th week at work! Define metrics
Lecture 53 7th week at work! Define events
Lecture 54 8th week at work: Drop in one metric!
Lecture 55 18 week at work: First results...
Section 10: Conclusion
Lecture 56 Conclusion
Product Managers who want to take data driven decisions,Product Managers who use analytics in their daily routine,Students who start or want to start a career as product managers,Students who wants to improve their skills in Data analytics tools like A/B test
Homepage

https://www.udemy.com/course/data-analytics-for-product-managers/

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