Course Description

Welcome to the exciting world of Big Data and Machine Learning Fundamentals on Google Cloud! This comprehensive course is designed to introduce you to Google Cloud's cutting-edge big data and machine learning products and services that power the data-to-AI lifecycle. You'll embark on a journey exploring the intricate processes, challenges, and immense benefits of constructing big data pipelines and machine learning models using Vertex AI on Google Cloud.

What You'll Learn

• Gain a deep understanding of the data-to-AI lifecycle on Google Cloud and its major big data and machine learning products
• Master the art of designing streaming pipelines using Dataflow and Pub/Sub
• Develop skills to analyze big data at scale with BigQuery
• Explore various options for building machine learning solutions on Google Cloud
• Understand the intricacies of a machine learning workflow and key steps using Vertex AI
• Hands-on experience in building a machine learning pipeline using AutoML

Prerequisites

This course is designed for beginners, and there are no specific prerequisites. However, a basic understanding of cloud computing concepts and familiarity with data analysis would be beneficial.

Course Content

• Introduction to Google Cloud's infrastructure and big data/ML products
• Streaming data management using Pub/Sub and Dataflow
• Data visualization with Looker and Data Studio
• BigQuery for data warehousing and BigQuery ML for custom ML models
• Overview of machine learning options on Google Cloud
• In-depth exploration of Vertex AI for ML project lifecycle management
• Practical application of AutoML for building ML models

Who This Course Is For

• Aspiring data engineers and data scientists
• IT professionals looking to transition into big data and machine learning
• Business analysts seeking to understand cloud-based data solutions
• Students and professionals interested in Google Cloud's data and AI capabilities
• Anyone curious about the intersection of big data and machine learning in cloud computing

Real-World Applications

• Design and implement big data solutions for businesses
• Create real-time data processing systems for various industries
• Develop predictive models for business decision-making
• Optimize data warehousing and analysis processes
• Build and deploy machine learning models for diverse applications
• Enhance data visualization and reporting capabilities
• Contribute to data-driven digital transformation initiatives

Syllabus

Each section of the syllabus is designed to provide a comprehensive understanding of the topic, with practical examples and hands-on exercises to reinforce learning. By the end of this course, you'll be well-equipped to tackle real-world big data and machine learning challenges using Google Cloud's powerful suite of tools and services.