Smart Analytics, Machine Learning, and AI on Google Cloud

Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs.
This is the fourth course of the Data Engineering on Google Cloud series.

Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud depending on the level of customization required. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs.

This is the fourth course of the Data Engineering on Google Cloud series.

• Introduction 1min
• Introduction to Analytics and AI 8mins
• Prebuilt ML Model APIs for Unstructured Data 12mins
• Big Data Analytics with Notebooks 7mins
• Production ML Pipelines with Kubeflow 10mins
• Custom Model building with SQL in BigQuery ML 12mins
• Custom Model Building with AutoML 24mins
• Summary 0mins
• Course Resources 0mins