Machine Learning on Google Cloud Duration: 4 Days

Course details

Module 1: Introduction to AI and Machine Learning on Google Cloud
• Overview of Machine Learning
• Examples of Machine Learning deployment specific to Google
• Business problems addressed by Machine Learning
• Introduction to the Vertex AI Platform - concepts, best practices, and labs.

Module 2: Launching into Machine Learning
• Introduction
• Get to Know Your Data: Improve Data through Exploratory Data Analysis
• Machine Learning in Practice
• Training AutoML Models Using Vertex AI
• BigQuery Machine Learning: Develop ML Models Where Your Data Lives
• Optimization
• Generalization and Sampling

Module 3: TensorFlow on Google Cloud
• Introduction to the TensorFlow ecosystem
• Design and Build an Input Data Pipeline
• Building Neural Networks with the TensorFlow and Keras API
• Training at Scale with Vertex AI

Module 4: Feature Engineering
• Introduction to Vertex AI Feature Store
• Raw Data to Features
• Feature Engineering
• Preprocessing and Feature Creation
• Feature Crosses - TensorFlow Playground
• Introduction to TensorFlow Transform

Module 5: Machine Learning in the Enterprise
• Introduction
• Understanding the ML Enterprise Workflow
• Data in the Enterprise
• Science of Machine Learning and Custom Training
• Vertex Vizier Hyperparameter Tuning
• Prediction and Model Monitoring Using Vertex AI
• Vertex AI Pipelines
• Best Practices for ML Development