Google Cloud Big Data and ML Essentials

This module provides an overview of the Big Data and Machine Learning Fundamentals course, introducing learners to the course structure and learning objectives. Students will understand the course goals and what they can expect to learn throughout the program.

Skills you'll gain

This module explores Google Cloud's infrastructure and introduces the key big data and machine learning products and services that support the data-to-AI lifecycle. Students learn about the fundamental components and their roles in big data and ML solutions.

Skills you'll gain

This module covers end-to-end streaming data pipeline management using Google Cloud services. Students learn about data ingestion with Pub/Sub, processing with Dataflow, and visualization techniques using Looker and Data Studio.

Skills you'll gain

This module focuses on BigQuery, Google's serverless data warehouse solution, and explores BigQuery ML. Students learn about the processes and key commands for building custom machine learning models within BigQuery.

Skills you'll gain

This module explores various approaches to building machine learning models on Google Cloud and introduces Vertex AI, Google's unified platform for ML projects. Students learn about different ML implementation options and their use cases.

Skills you'll gain

This module covers the three key phases of the machine learning workflow in Vertex AI: data preparation, model training, and model preparation. Students gain hands-on experience building a machine learning model using AutoML.

Skills you'll gain

This module reviews all the topics covered throughout the course and provides additional resources for continued learning. Students consolidate their knowledge and receive guidance on further steps in their learning journey.

Skills you'll gain