CÔNG TY TNHH TRAINOCATE VIỆT NAM
GCPBD - Google Cloud Platform Big Data and Machine Learning Fundamentals

GCPBD - Google Cloud Platform Big Data and Machine Learning Fundamentals

GCPBD - Google Cloud Platform Big Data and Machine Learning Fundamentals

Overview

Duration: 1.0 day

This certification & training course will introduce you to Google Cloud's big data and machine learning functions. You'll begin with a quick overview of Google Cloud and then dive deeper into its data processing capabilities.

Objectives

  • Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud.
  • Use Cloud SQL and Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud.
  • Employ BigQuery and Cloud SQL to carry out interactive data analysis.
  • Choose between different data processing products in Google Cloud.
  • Create ML models with BigQuery ML, ML APIs, and AutoML.

Content

Module 1: Introducing Google Cloud Platform

  • Google Platform Fundamentals Overview.
  • Google Cloud Platform Big Data Products.
  • Lab: Sign up for Google Cloud Platform.

Module 2: Compute and Storage Fundamentals

  • CPUs on demand (Compute Engine).
  • A global file system (Cloud Storage).
  • Cloud Shell.
  • Lab: Set up an Ingest-Transform-Publish data processing pipeline.

Module 3: Data Analytics on the Cloud

  • Stepping stones to the cloud.
  • Cloud SQL: your SQL database on the cloud.
  • Lab: Importing data into CloudSQL and running queries.
  • Spark on Dataproc.
  • Lab: Machine Learning Recommendations with Spark on Dataproc.

Module 4: Scaling Data Analysis

  • Fast random access.
  • Datalab.
  • BigQuery.
  • Lab: Build a Machine Learning Dataset.

Module 5: Machine Learning

  • Machine Learning with TensorFlow.
  • Lab: Carry out ML with TensorFlow.
  • Pre-built models for common needs.
  • Lab: Employ ML APIs.

Module 6: Data Processing Architectures

  • Message-oriented architectures with Pub/Sub.
  • Creating pipelines with Dataflow.
  • Reference architecture for real-time and batch data processing.

Module 7: Summary

  • Why GCP?.
  • Where to go from here.
  • Additional Resources

Audience

  • Data analysts, data scientists, and business analysts who are getting started with Google Cloud.
  • 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.
  • Executives and IT decision makers evaluating Google Cloud for use by data scientists.

Prerequisites

Roughly one year of experience with one or more of the following:

  • A common query language such as SQL.
  • Extract, transform, and load activities.
  • Data modeling.
  • Machine learning and/or statistics.
  • Programming in Python.

Certification

Associated with Machine Learning Engineer & Professional Data Engineer Certification.

Lịch khai giảng

Form đăng ký

Bằng cách nhấn nút "ĐĂNG KÝ", tôi hoàn toàn đồng ý với Chính sách bảo mật

Các khóa đào tạo Google Cloud khác

GCPPCA-T - Google Cloud Certified Professional Cloud Architect

This Track includes : Google Cloud Platform Fundamentals: Core Infrastructure - GCPCIN- 1 Day Architecting with Google Compute Engine - GCPGCE - 3 Days Architecting with Google Kubernetes Engine - GCPGKE - 3 Days Architecting with Google Cloud Platform: Design and Process -GCPDNPS - 2 Days Preparing for the Professional Cloud Architect Examination -GCPPCA - E - 1 Day Google Cloud Platform Fundamentals: Core Infrastructure – GCPCIN This one-day instructor-led certification & training course provides an overview of GoogleCloud Platform products and services. Through a combination of presentations, demos, and hands-on labs, participants learn the value of Google Cloud Platform and how to incorporate cloud-based solutions into business strategies. Architecting with Google Compute Engine – GCPGCE This three-day instructor-led certification & training course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud Platform, with a focus on Compute Engine. Through a combination of presentations, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems, and application services. This course also covers deploying practical solutions including securely interconnecting networks, customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.
10 ngày

Bản quyền thuộc về Trainocate Việt Nam

back to top