October 17, 2024 | 2 PM – 6 PM (CET)

Free GCP Big Data and Machine Learning Fundamentals

This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

95

Days

17

Hours

37

Minutes

Reserve a spot

for October 17, 2024

Date

Oct 17, 2024

Time

2 PM to 6 PM (CET)

Location

Online – Google Meet

Language

English

Speakers

4

Speaker

Meet the cloud expert who will share his knowledge and expertise with you this afternoon.

Martijn van de Grift

Practice Lead & Authorized Cloud Trainer + Google Cloud Practice CTO

Who Should Attend

This course if for

  1. Data Analysts, Data Engineers, Data Scientists, and ML Engineers who are getting started with Google Cloud.
  2. Individuals responsible for designing pipelines and architectures for data processing, creating and maintaining machine learning and statistical models, querying datasets, visualizing query results, and creating reports.
  3. Executives and IT decision-makers evaluating Google Cloud for use by data scientists.

Objectives

  • Identify the data-to-AI lifecycle on Google Cloud and the major products of big data and machine learning.
  • Design streaming pipelines with Dataflow and Pub/Sub.
  • Analyze big data at scale with BigQuery.
  • Identify different options to build machine learning solutions on Google Cloud.
  • Describe a machine learning workflow and the key steps with Vertex AI.
  • Build a machine learning pipeline using AutoML.

What You Need to Know

Prerequisites

This training is open to all.

Certification

This course is not associated with any Google Cloud certification, but attendees who successfully pass the Qwiklabs receive a certificate of attendance.

Program

The course includes presentations, demonstrations, and hands-on labs.

Module 1

Big Data and Machine Learning on Google Cloud

  • Identify the different aspects of Google Cloud’s infrastructure
  • Identify the big data and machine learning products on Google Cloud

Module 2

Data Engineering for Streaming Data

  • Describe an end-to-end streaming data workflow from ingestion to data visualization
  • Identify modern data pipeline challenges and how to solve them at scale with Dataflow
  • Build collaborative real-time dashboards with data visualization tools

Module 3

Big Data with BigQuery

  • Describe the essentials of BigQuery as a data warehouse
  • Explain how BigQuery processes queries and stores data
  • Define BigQuery ML project phases
  • Build a custom machine learning model with BigQuery ML

Module 4

Machine Learning Options on Google Cloud

  • Identify different options to build ML models on Google Cloud
  • Define Vertex AI and its major features and benefits
  • Describe AI solutions in both horizontal and vertical markets

Module 5

The Machine Learning Workflow with Vertex AI

  • Describe a ML workflow and the key steps
  • Identify the tools and products to support each stage
  • Build an end-to-end ML workflow using AutoML

Module 6

Summary

  • Recap of key learning points
  • Resources

Reserve your spot

Reserve your spot and join this Free GCP Big Data and Machine Learning Fundamentals via Google Meet.