Machine Learning in Google Cloud

Overview

Delivery method

Virtual classroom

Duration

5 days

Audience

Information Technology Specialists

Description

Fees are associated with each registration. Please be mindful of your registration and commit to honouring your registration. Any cancellation after the registration period will incur fees that SSC will have to cover. To avoid this, please cancel at least 12 business days prior to the course start date.

This course introduces the artificial intelligence (AI) and machine learning (ML) offerings on Google Cloud that support the data-to-AI lifecycle through AI foundations, AI development, and AI solutions.

You learn how to build AutoML models without writing a single line of code; build BigQuery ML models using SQL, and build Vertex AI custom training jobs by using Keras and TensorFlow. You also explore data preprocessing techniques and feature engineering.

Learning Objectives 

By the end of this course, you will be able to:

• Describe the technologies, products, and tools to build an ML model, an ML pipeline, and a Generative AI project;
• Understand when to use AutoML and BigQuery ML;
• Create Vertex AI-managed datasets;
• Add features to the Vertex AI Feature Store;
• Describe Analytics Hub, Dataplex, and Data Catalog;
• Describe how to improve model performance;
• Create Vertex AI Workbench user-managed notebook, build a custom training job, and deploy it by using a Docker container;
• Describe batch and online predictions and model monitoring;
• Describe how to improve data quality and explore the data;
• Build and train supervised learning models;
• Optimize and evaluate models by using loss functions and performance metrics;
• Create repeatable and scalable train, eval, and test datasets;
• Implement ML models by using TensorFlow or Keras;
• Understand the benefits of using feature engineering;
• Explain Vertex AI Model Monitoring and Vertex AI Pipelines.

Target Audience

• Aspiring machine learning data analysts, data scientists, and data engineers;
• Learners who want exposure to ML and use Vertex AI, AutoML, BigQuery ML, Vertex AI Feature Store, Vertex AI Workbench, Dataflow, Vertex AI Vizier for hyperparameter tuning, and TensorFlow/Keras.

Prerequisite(s)

• Some familiarity with basic machine learning concepts
• Basic proficiency with a scripting language, preferably Python

Notes

The Digital Enterprise Skilling (DES) program provides Shared Services Canada (SSC) employees with the knowledge and skills required to accelerate digital adoption, improve IT services delivery, and adapt to the workforce’s needs of the future. If you have not registered as an SSC Digital Enterprise Skilling (DES) participant yet, sign up here: DES Learner's Portal _ Portail de l'apprenant du programme CNE - Power Apps