Product Analytics and AI
Beginner
Online
4 Weeks
6,638 INR
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Compare Quick Facts
Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
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English | Self Study | Video and Text Based |
Courses and Certificate Fees
Certificate Availability | Certificate Providing Authority |
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yes | Coursera |
Product Analytics and AI Fees structure is as follows:
Description | Amount |
Course Fees (1 Month) | ₹ 6,638/- |
Course Fees (3 Month) | ₹ 13,276 /- (4,425 per month) |
Course Fees (6 Month) | ₹ 19,915 /- (3,319 per month) |
The Syllabus
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
- 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
Reading
- Course Overview & Requirements
Assignments
- Introduction and Customer Analytics
- Customer Analytics
Discussion prompts
- Tools & Tips for Story Mapping
- Focal Points: Trent the Technician
- Looking Forward to Upcoming Topics
Videos
- Lean Startup and the Demand Hypothesis
- Demand Testing at Enable Quiz
- Designing Experiments
- Experiment Design with MVPs
- Designing User Habits: The Hook Framework
- Five Experiment Charters
- The Fake Feature Test•4 minutes
- 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
Assignments
- Testing Demand and Experiment Patterns
- Testing Motivations with MVPs
- Experiments
- Testing Features
Discussion prompt
- Fake Feature Tests & Your Experience
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
- 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
Assignments
- Qualitative and Quantitative Analytics
- Testing Analytics
- User Stories & Analytics
- A/B Testing
Peer review
- Creating a Testable Solution
Discussion prompts
- Google Analytics & Alex's Website
- Tools & Tips for A/B Testing
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
Assignments
- Analytics and Data Science
- Data Science
- Data Executions
- Data Science IRL
Discussion prompts
- Data Science & Your Experience
- Tips for Working with a Data Science Team
Articles