Unit 1: Intro to Machine Learning
Unit 2: Regression vs. Classification
Unit 3: Model Evaluation
ML for Product Managers: Integrating into Core Platform
Empowering Product Managers to leverage Machine Learning for core platform innovation, from identifying opportunities to ethical deployment.
Unit 1: Finding the Fit: Where ML Meets Product
Unit 2: Framing the Problem: From Product to ML
Unit 3: Prioritization: Impact and Alignment
Unit 1: Data Availability and Quality
Unit 2: Model Complexity and Resource Requirements
Unit 3: Impact on Key Product Metrics
Unit 1: Understanding ML Team Roles
Unit 2: The ML Development Workflow
Unit 3: ML Tools and Platforms
Unit 1: Understanding Basic Metrics
Unit 2: Advanced Metrics and Applications
Unit 3: Applying Metrics to Product Goals
Unit 1: Overview of the ML Product Lifecycle
Unit 2: Data Collection and Preparation
Unit 3: Model Training and Evaluation
Unit 4: Deployment, Monitoring, and Iteration
Unit 5: Advanced Topics and Best Practices
Unit 1: Understanding Bias in ML
Unit 2: Fairness Metrics and Assessment
Unit 3: Mitigating Bias and Ensuring Fairness