Welcome

• For "official" communication we are use Moodle.
• For informal and in-class communication, we use Slack.
• On this page you will find additional courseware, which accompanies the course.
• You will find the scripts we use in this course on this github page.
• There are a set of recap/summary videos on our Youtube channel.
• In case you need help, you can find the instructor's and the TA's contact details at the bottom of this page.

Syllabus

Data Engineering 2: Cloud Computing

Prerequisites

R programming

SQL Knowledge

Linux command-line knowledge

Course description

This is a technology-focused course on cloud computing systems. Current Data Analytics Architectures often work with an amount of data that cannot be fit on a single computer. Even companies that work with reasonably small datasets are expecting rapid growth, so they prefer to use data analytics solutions that are easy to distribute and scale when needed. In this course you will get an overview and hands-on experience with basic cloud technologies as well as Serverless solutions in the cloud. You will see how cloud computing can help you quickly iterate and scale your data analytics infrastructure and how it can help you reduce operational costs.

Course schedule and materials for each session

1. Basics of Internet. TCP/IP, Servers, Ports, Firewalls
2. Basics of Cloud Computing using Amazon Web Services (AWS): Storage and Virtual Machines
3. Serverless solutions in the cloud. Using AWS programatically
4. The concept of the Data Lake. Amazon Athena. Building an end-to-end data pipeline.

Acknowledgements

Many of the course materials were created by Miklos Petridisz

Contact