This is a technology-focused course on cloud computing and cloud-based data analytics tools.
Current Data Analytics Architectures often work with an amount of data that cannot be fit on a single computer; furthermore, companies tend to avoid large upfront investments in hardware. Even companies that work with reasonably small datasets expect rapid growth, so they prefer to use data analytics solutions that scale when needed. In this course, you will get an overview and hands-on experience with Amazon Web Services, one of the leading cloud solutions. You will also see how cloud computing can help you quickly iterate and scale your data analytics infrastructure and how it can help you reduce operational costs.
The course includes a starter lecture where students can familiarize themselves with client-server architectures, secure internet communication, and digital signatures.
At the end of this course, you will have an overview of Cloud technologies applied in modern businesses. You will have a general understanding of how these technologies work, and you will be able to reason about when to use or not to use them. You will be hands-on with Amazon Web Services.
Once you complete the assignments for this course, you will be hands-on with the following technologies:
- Internet Basics
- Public Key Encryption, Digital Signatures
- Fundamental Cloud Computing concepts: Storage, Virtual Machines
- Serverless Services for image and text recognition
- Amazon Athena: An SQL-based analytics tool in the cloud.
Other outcomes - see syllabus
Assignments (60%)
Exam (40%)
Students shall not miss more than two lectures. Failing to do so will yield an administrative fail grade.
To pass, students will need to get at least 60% of the overall grade. Failure to do so will yield a Fail grade.