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  • PRIVATE BATCH
  • PUBLIC PROGRAM
  • ON DEMAND
  • BLENDED

Course Details

  • Course Overview
  • Skills Gained
  • Who Can Benefit
  • Prerequisite
  • Syllabus

This one-day GCP instructor-led class introduces students to the big data capabilities of Google Cloud Platform. With a combination of demos, presentations, and hands-on labs, members will get an overview of the Google Cloud platform and also a detailed view of the data processing and machine learning capabilities. This training showcases the flexibility, ease, and power of big data solutions on Google Cloud Platform.

  • Find the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform.
  • Effectively use Cloud SQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.
  • Employ ML APIs
  • Train and use a neural network using TensorFlow.
  • Employ BigQuery and Cloud Datalab to bring out interactive data analysis.
  • Choose between completely different data processing products on the Google Cloud Platform.

This course is designed for the following:

  • Data scientists, Data analysts, Business analysts who are getting started with Google Cloud Platform.
  • Individuals who are 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.
  • IT decision makers and executives evaluating Google Cloud Platform to be used by data scientists.

To get the foremost of out of this course, participants ought to have:

 

  • Basic knowledge with common query language such as SQL.
  • Developing applications using a common programming language such Python.
  • Experience with data modeling, extract, transform, load activities.
  • Experience with machine learning and/or statistics.

1. Introducing Google Cloud Platform

  • Google Platform Fundamentals Overview.
  • Google Cloud Platform Big Data Products.

2. Compute and Storage Fundamentals

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

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.

4. Scaling Data Analysis

  • Fast random access.
  • Datalab.
  • BigQuery.
  • Lab: Build machine learning dataset.

5. Machine Learning

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

6. Data Processing Architectures

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

7. Summary

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



Audience

  • Business Analyst
  • Data Scientist
  • Data Professionals

Public Program Schedule

Course Name Duration Brochure Location Schedule Enroll
There is no upcoming Public Batch Schedule, you can ask for Private Batch or for On-Demand Learning

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FAQ

  • What is a Google Cloud certification?
  • Why should I get a Google Cloud certification?
  • How long is a Google Cloud certification valid?
  • What is the recertification policy?
  • Why do I need to recertify?
  • How do I pay?
  • What are your cancellation & refund policy?

Google Cloud's certification program gives Google Cloud users, customers and partners a way to demonstrate their technical skills in a particular job role or technology. Individuals are assessed using a variety of rigorously developed industry standard methods to determine whether they meet Google Cloud's proficiency standards.

Google Cloud certifications give you benchmarks for your professional development. They help you gauge your skill set against your peers and demonstrate your value to hiring managers.

Unless explicitly stated in the detailed exam descriptions, all Google Cloud certifications are valid for two years from the date certified. Candidates must recertify in order to maintain their certification status.

Unless explicitly stated in the detailed exam descriptions, all Google cloud certifications are valid for two years from the date certified. Candidates must recertify in order to maintain their certification status and certificate number.

Google technology changes frequently. We require recertification to ensure you're maintaining your skills.

We accept all modes of payment. If you are being nominated by your organization, your organization need to release PO before the course start date. If you are an individual you can pay through credit / debit cards, online transfer (RTGS/NEFT) to our account 7 days prior to the course start date.

  • In a highly unlikely event of cancellation of batch from our end, we shall refund 100% that is paid by you. If client choose to cancel for any reasons, below is the terms.
  • If you cancel or reschedule your registration 5 or more calendar days before the scheduled start date of the class – No cancellation charges
  • If you cancel or reschedule your registration less than 5 calendar days before the scheduled start date of the class – cancellation charges 100% of the course fee
  • If you do not show up for the event, or cancel on the day of the event - cancellation charges 100% of the course fee

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