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 Vertex AI. Learners will get hands-on experience building machine learning models on Google Cloud using QwikLabs.

• Differentiate between ML, AI and Deep Learning.
• Discuss the use of ML API’s on unstructured data.
• Execute BigQuery commands from Notebooks.
• Create ML models by using SQL syntax in BigQuery.
• Create ML models without coding using AutoML.

• To benefit from this course, participants should have completed “Google Cloud Big Data and Machine Learning Fundamentals” or have equivalent experience.