Machine Learning with BigQuery Online Course

Machine Learning with BigQuery Online Course

The Machine Learning with BigQuery online course equips you with essential skills for one of today’s most sought-after fields: applied machine learning. The course highlights the power of supervised learning, where models are trained on existing datasets, and emphasizes the need for scalable solutions beyond personal devices. Using Google Cloud Platform's BigQuery—a serverless, petabyte-scale data warehouse—you'll learn to manage structured datasets, execute lightning-fast SQL queries, and focus on advanced analytics without worrying about infrastructure. The curriculum introduces BigQuery ML and guides you in building machine learning models at scale. By course completion, you'll be adept at utilizing GCP's managed services to drive impactful data-driven insights.

Key Benefits

• Gain a solid foundational understanding of Google Cloud Platform, with a specific focus on BigQuery and its applications.
• Explore the history, architecture, and practical use cases of BigQuery, tailored for machine learning engineers and data professionals.
• Access curated learning materials and resource files designed to enhance and reinforce your knowledge throughout the course.

Target Audience

This course is ideal for individuals seeking to develop real-world machine learning models at scale using BigQuery, one of the most widely utilized services on Google Cloud Platform (GCP). Designed as a mid-level course, it is best suited for those with foundational experience in SQL and Python, which will enable participants to maximize their learning and application of the course material.

Learning Objectives

• Gain in-depth knowledge of BigQuery's capabilities and its applications in machine learning.
• Explore the core functionalities of GCP with a focus on BigQuery's architecture and operations.
• Learn the principles of applied machine learning under the guidance of an experienced machine learning engineer.
• Master the process of creating and deploying machine learning models at scale using BigQuery.
• Familiarize yourself with BigQuery ML and its role in enabling efficient machine learning workflows.
• Develop a strong foundation in applied machine learning concepts to address real-world challenges effectively.

Course Topics

The Machine Learning with BigQuery Online Course covers the following topics - 

Domain 1 - Introduction

• Overview of the Course
• The Concept of Scaling Out Instead of Up
• Google's Scaled-Out Data Revolution
• Demo: Setting Up an Account on Google Cloud Platform

Domain 2 - BigQuery Basics

• Understanding BigQuery: Definition and Capabilities
• How BigQuery Stores Structured Data
• Benefits of Parallel Execution
• Demo: Navigating the BigQuery Web UI
• Clarifying What BigQuery Is Not
• Overview of BigQuery’s Technology Stack
• Demo: Basic Navigation Techniques

Domain 3 - Introduction to Applied Machine Learning

• Core Concepts of Machine Learning
• Exploring Three Core Machine Learning Careers
• The Applied Machine Learning Workflow
• Types of Machine Learning (Supervised, Unsupervised, etc.)
• The Importance of Python in Machine Learning
• Setting Up Python:
  • Windows Installation
  • MAC Installation
• Introduction to Arrays
• Navigating Jupyter Notebooks for Data Science

Domain 4 - Machine Learning Libraries

• Overview of Core Machine Learning Libraries
• Demo: Using Core Machine Learning Libraries
• Sourcing and Preparing Data
• Exploratory Data Analysis and Insights
• Data Cleansing and Preprocessing Techniques
• Demo: Building and Evaluating Machine Learning Models

Domain 5 - Classification and Regression

• Introduction to Linear Regression Techniques
• Demo: Linear Regression in Action
• Fundamentals of Classification Models
• Demo: Implementing Classification Models
• Exploring Artificial Neural Networks and Their Applications

Domain 6 - Machine Learning with BigQuery

• Managing Datasets and Tables in BigQuery
• Demo: Working with Datasets and Tables
• Demo: Using Cloud Datalab for Machine Learning
  • Titanic Dataset Modeling
  • Iris Dataset Modeling
• Scaling Cloud Datalab for Large-Scale Analysis
• Introduction to BigQuery ML
• Demo: Binary Logistic Regression with BigQuery ML
• Setting Up the Google Cloud SDK
• Demo: Navigating with gsutil
• Demo: Segmenting Datasets for Advanced Analytics