---
source_url: "https://www.sela.co.il/courses/CPB400/info?courseCode=CPB400&branchName=165"
title: Data Engineering on Google Cloud Platform
mirrored_at: 2026-08-19T01:03:30.681Z
host: www.sela.co.il
cited_in_42a: true
mirror_canonical: "https://index.42a.ai/www.sela.co.il/courses/CPB400/info__q__courseCode_CPB400__branchName_165"
---

> **Original source:** https://www.sela.co.il/courses/CPB400/info?courseCode=CPB400&branchName=165

4

sessions

Description

This four-day instructor-led class provides participants a hands-on introduction to designing and building data processing systems on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn how to design data processing systems, build end-to-end data pipelines, analyze data and carry out machine learning. The course covers structured, unstructured, and streaming data.

Intended audience

Extracting, Loading, Transforming, cleaning, and validating data Designing pipelines and architectures for data processing Creating and maintaining machine learning and statistical models Querying datasets, visualizing query results and creating reports

## Topics

Module 1: Google Cloud Dataproc Overview

Module 2: Running Dataproc Jobs

Module 3: Integrating Dataproc with Google Cloud Platform

Module 4: Making Sense of Unstructured Data with Google’s Machine Learning APIs

Module 5: Serverless data analysis with BigQuery

Module 6: Serverless, autoscaling data pipelines with Dataflow

Module 7: Getting started with Machine Learning

Module 8: Building ML models with Tensorflow

Module 9: Scaling ML models with CloudML

Module 10: Feature Engineering

Module 11: Architecture of streaming analytics pipelines

Module 12: Ingesting Variable Volumes

Module 13: Implementing streaming pipelines

Module 14: Streaming analytics and dashboards

Module 15: High throughput and low-latency with Bigtable