Overview

A Professional Data Engineer enables data-driven decision making by collecting, transforming, and publishing data. A Data Engineer should be able to design, build, operationalize, secure, and monitor data processing systems with a particular emphasis on security and compliance; scalability and efficiency; reliability and fidelity; and flexibility and portability. A Data Engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.

Certification Roadmap:
  • STEP 1: Google Cloud Platform Fundamentals: Big Data and Machine Learning - 1 Day
  • STEP 2: Data Engineering on Google Cloud Platform - 4 Days
  • Exam: Google Cloud Certified - Professional Data Engineer

Learning Outcome

At the end of this course, participants will understand:
  • Identify the purpose and value of the key Big Data and Machine Learning products in Google Cloud
  • Use CloudSQL and Cloud 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
  • Design and build data processing systems on Google Cloud Platform
  • Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow
  • Derive business insights from extremely large datasets using Google BigQuery
  • Train, evaluate and predict using machine learning models using Tensorflow and Cloud ML
  • Leverage unstructured data using Spark and ML APIs on Cloud Dataproc
  • Enable instant insights from streaming data

Who should Attend?

This class is intended for the following participants:
  • Data Analyst
  • Data Engineer
  • Data warehouse Professional
  • Big Data Engineer
  • Machine Learning Professional
  • Artificial Intelligence
  • Data Analyst

Eligibility Criteria

To get the most of out of this course, participants should have:
  • Basic knowledge of SQL is useful but not required
This course is endorsed under Critical Infocomm Technology Resource Programme Plus (CITREP+) Programme.
To find out more about CITREP+ Funding, please refer to Programme Support under CITREP+ page

Information as accurate as of 6 August 2020