Google Cloud End to End Data Engineering Projects
Master End-to-End Data Engineering: Real-Time Streaming, AI Integrations, and High-Performance Systems! Dive into hands-on projects, expert-guided tutorials, and cutting-edge technologies for a standout career in data engineering.
4.0
(2)
25 learners
What you'll learn
- Understand and implement real-time streaming with Google Cloud for data engineering projects
- Learn how to perform real-time socket streaming using Apache Spark
- Master the use of Apache Airflow alongside Spark, Pyspark, Java, and Scala for data engineering
- Develop skills to build and optimize high-performance, real-time analytics databases
This course includes
- 47.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 31 lessons • 47.5 hours of video
Mastering End-to-End Data Engineering Projects
31 lessons
• 47.5 hours
Mastering End-to-End Data Engineering Projects
31 lessons
• 47.5 hours
- Google Cloud Realtime Streaming | End to End Data Engineering Project 01:28:23
- Realtime Socket Streaming with Apache Spark | End to End Data Engineering Project 01:42:25
- Apache Airflow with Spark, Pyspark, Java, Scala for Data Engineers || Full Course 01:08:39
- Apache Flink For Analytics | End to End Data Engineering Project 58:06
- Realtime Voting System | End-to-End Data Engineering Project 02:18:35
- Kubernetes for Modern Data Engineering: An End to End Data Engineering Project 01:25:18
- End to End Realtime Streaming with Unstructured Data | Get Hired as an Experienced Data Engineer 02:30:32
- Real Estate End to End Data Engineering using AI 02:08:27
- Building Data Lakehouse from Scratch - End to End Data Engineering Project 55:06
- Realtime Streaming with Data Lakehouse - End to End Data Engineering Project 01:09:39
- Realtime Algorithmic Trading with Apache Flink | End to End Data Engineering Project 01:41:35
- Query Optimisation for Data Engineers | End to End Walkthrough 51:56
- Decodable vs AWS Managed Service for Apache Flink (MSF) - End to End Data Engineering Project 02:33:43
- Realtime Stock Market Anomaly Detection using ML Models | An End to End Data Engineering Project 01:02:01
- Building a High Performance Real-Time Analytics Database - End to End Data Engineering Project 01:10:52
- 1.2 Billion Records Per Hour High Performance Kafka and Spark - End to End Data Engineering Project 02:17:32
- End to End Monitoring of High Performance Systems - A Data Engineering Project PART 1 28:19
- End to End Monitoring with Prometheus, Grafana, Apache Kafka and Spark - A Data Engineering Project 20:08
- Elasticsearch for High Throughout Systems - 1 Billion records! 34:49
- Build Realtime Fraud Detection AI from Scratch - End to End Machine Learning Project - Part 1 04:51:14
- Apache Iceberg Explained in 10 Minutes – Everything You Need to Know! 11:55
- Build Churn Training and Inference AI from Scratch - End to End Machine Learning Project - Part 1 50:43
- Building Self-Healing Data Pipeline - End to End Data Engineering Project 01:34:13
- Realtime Logs Processing with Apache Airflow, Kafka and Elasticsearch - End to End Data Engineering 02:03:26
- Build a Fraud Detection AI from Scratch: End-to-End Machine Learning Project 05:55:42
- Build Churn Training and Inference AI from Scratch - End to End Machine Learning Project 01:54:31
- Apache Spark on Kubernetes: The RIGHT Way (No Master/Worker Clusters Needed) 57:54
- Setting up Apache Spark Master Worker Architecture 07:12
- Monitoring High Performance Systems - An End to End Data Engineering Project 01:23:29
- Setting up Apache Projects Architectures 03:20
- Build a Production-Ready Real-Time CDC Pipeline (Debezium + Kafka + Postgres) 01:02:54
Related learning topics
Take this course with you
Download the app to continue lessons from your phone anytime.
