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Data Science Fundamentals For Product Managers
Introduction
Setting the context (1:13)
Learning Objectives
Course Overview (0:41)
Chapter 1: Understanding Data Science
Learning Objective
1.1: What is Data Science? (0:58)
1.2: What are “Data Science enabled Products”? (2:28)
1.3: Big Data Landscape (1:52)
1.4: Data Science Basics & Machine Learning (3:01)
Chapter Quiz
Chapter 2: Data Science Algorithms and Analysis Methods
Learning Objective
2.1: Analysis Methods (0:42)
2.2: Descriptive Analysis (1:01)
2.3: Predictive Analysis & Prescriptive Analysis (3:06)
2.4: Big Data Terminologies (2:14)
2.5: Data Science Algorithms (2:25)
2.6: Principal Component Analysis (0:54)
2.7: K-Means Clustering (1:10)
2.8: Association Rules (1:46)
2.9: Page Rank Algorithm (0:32)
2.10: Regression Analysis (0:50)
2.11: K-Nearest Neighbors (1:15)
2.12: Decision Trees (1:22)
Chapter Quiz
Chapter 3: Building Products With Data Science
Learning Objective
3.1: Data Science Project (2:39)
3.2: Data Format (1:37)
3.3: Variable Types (0:39)
3.4: Variable Selection (1:07)
3.5: Feature Engineering (0:42)
3.6: Algorithm Selection (0:57)
3.7: Parameter Tuning (0:28)
3.8: Evaluating Results (1:37)
3.9: Building Products (1:28)
3.10: Invisible AI As The Best AI (2:02)
3.11: Actionable Insights (1:15)
3.12: Your Users Are Not Data Scientists (1:33)
3.13: Design is AI's Best Friend (2:13)
3.14: Managers Deserve Less (1:29)
3.15: Don't Visualize Data (1:02)
3.16: Be The QA You Want To See (0:36)
3.17: Ask Your Users: Back Testing (1:52)
3.18: Data Science Pitfalls (2:33)
Chapter Quiz
Chapter 4: Engaging With Data Science Teams
Learning Objective
4.1: PMs Should Engage With Data Scientists (2:01)
4.2: Product Marketing & Data Science (3:10)
4.3: What Is A Data Smart Product Manager? (1:51)
4.4: Personas In The Data Science Arena (1:50)
Chapter Quiz
Chapter 5: Getting Started With Essentials Of Data Science
Learning Objective
5.1: Data Science Essentials (0:53)
5.2: Linear Regression (1:09)
5.3: Scatter Plot (0:37)
5.4: Regression Equation (0:42)
5.5: Regression Result (3:25)
5.6: Regression & Data Science (0:55)
5.7: Cluster Analysis (3:50)
Chapter Quiz
Chapter 6: Data Strategy and Visualization
Learning Objective
6.1: What Is Data Strategy? (4:16)
6.2: What Are Some Examples Of Divergent Strategies? (1:06)
6.3: Data Visualization (2:31)
6.4: Time Series Data (0:50)
6.5: Cartographic Data (0:39)
6.6: Financial Chart (0:39)
6.7: Interactive Visualization (0:42)
6.8: Heat Maps (0:44)
6.9: Visualizing Scale (0:45)
6.10: Music (0:26)
6.11: Five ThirtyEight Visualization (0:42)
Chapter Quiz
Conclusion
Summary (1:36)
Final Exam
1.2: What are “Data Science enabled Products”?
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