Machine Learning on Google Cloud (MLGC)

 

Course Overview

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. It explores the technologies, products, and tools available to build an ML model, an ML pipeline, and a generative AI project. 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.

Who should attend

  • 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, TensorFlow/Keras.

Prerequisites

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

Course Objectives

  • 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 your 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.

Follow On Courses

Prices & Delivery methods

Online Training

Duration
5 days

Price
  • on request
Classroom Training

Duration
5 days

Price
  • on request

Schedule

English

Time zone: Gulf Standard Time (GST)

Online Training This is a FLEX course. Time zone: Gulf Standard Time (GST)
Online Training View the exact training days 4 days This is a FLEX course. Time zone: Gulf Standard Time (GST)

1 hour difference

Online Training This is a FLEX course. Time zone: Eastern European Summer Time (EEST)

2 hours difference

Online Training 4 days Time zone: Central European Summer Time (CEST)

3 hours difference

Online Training 4 days Time zone: Central European Time (CET)

4 hours difference

Online Training Time zone: UTC+8
Online Training Time zone: UTC+8

10 hours difference

Online Training Time zone: Central Standard Time (CST)
Online Training Time zone: Central Standard Time (CST)

11 hours difference

Online Training Time zone: Pacific Daylight Time (PDT)
Online Training Time zone: Pacific Daylight Time (PDT)
Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.
This is a FLEX course, which is delivered both virtually and in the classroom.

United Arab Emirates

Dubai
Dubai View the exact training days 4 days
This is a FLEX course, which is delivered both virtually and in the classroom.