Introduction to Course and Series-Series Preview and Course Introduction
Course series preview
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Course introduction
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What It Means to be AI-First-What it Means to be AI First: Module Introduction
Introduction
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What It Means to be AI-First-Machine Learning on Google Cloud
What is ML?
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What problems can it solve?
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Activity intro: Framing a machine learning problem
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Activity: Framing a machine learning problem
Activity solutions: Framing a machine learning problem
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Infuse your apps with ML
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Build a data strategy around ML
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Resources: What It Means to Be AI First
How Google Does ML-How Google Does Machine Learning
Introduction
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ML Surprise
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The secret sauce
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ML and business processes
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The path to ML
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A closer look at the path to ML
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End of phases deep dive
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Resources: How Google does ML
Machine Learning Development with Vertex AI-ML Development with Vertex AI: Module Introduction
Introduction
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Machine Learning Development with Vertex AI-Moving from Experimentation to Production
Moving from experimentation to production
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Machine Learning Development with Vertex AI-Vertex AI
Components of Vertex AI
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Getting Started with Google Cloud Platform and Qwiklabs
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Lab intro: Using an image dataset to train an AutoML model
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Lab demo: Using an image dataset to train an AutoML model
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Lab intro: Training an AutoML video classification model
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Lab demo: Training an AutoML video classification model
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Tools to interact with Vertex AI
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Resources: Machine Learning Development with Vertex AI
Machine Learning Development with Vertex Notebooks-ML Development with Vertex Notebooks: Module Introduction
Introduction
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Machine Learning Development with Vertex Notebooks-ML Development with Vertex Notebooks
Machine learning development with Vertex Notebooks
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Resources: Machine Learning Development with Vertex Notebooks
Best Practices for Implementing Machine Learning on Vertex AI-Best Practices for Implementing Machine Learning on Vertex AI: Module Introduction
Introduction
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Best Practices for Implementing Machine Learning on Vertex AI-Best Practices for Implementing Machine Learning on Vertex AI
Best practices for machine learning development
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Data preprocessing best practices
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Best practices for machine learning environment setup
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Responsible AI Development-Responsible AI Development: Module Introduction
Introduction
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Responsible AI Development-Machine Learning and Human Bias
Overview
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Human biases lead to biases in ML models
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Biases in data
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Responsible AI Development-Equality in Metrics and Data
Evaluating metrics with inclusion for your ML system
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Equality of opportunity
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How to find errors in your dataset using Facets
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Resources: Responsible AI Development
Summary-Course Summary
Summary
Resource: All quiz questions
Resource: All readings
Resource: All slides