Week 0 ~ June 4 - June 10

In the week prior to the first project, learners should sign up and become familiar with course tools such as TheProjectZone, Open Learning Initiative(OLI), Piazza, Github, and create an account with each cloud provider AWS, Azure, GCP.

Week 1 ~ June 11 - June 17

Learners will learn the benefits and tradeoffs of running programs in parallel, using AWS EMR, versus sequential on a large dataset. Learners will have to perform data processing and analytics on a large data set using resources provisioned in AWS within particular cost constraints.

Week 2 ~ June 18 - June 24

In this project, learners will learn about cloud elasticity using virtual machines. Learners will be first tasked with developing their own elastic services for a dynamically changing load scenario using AWS APIs. Learners will then work with the Load Balancing and Auto Scaling services on AWS to mitigate varying loads on the server.

Week 3 ~ June 25 - July 1

Learners will build a hands-on in-browser programming web service using Docker Containers and Kubernetes on multiple cloud platforms (Azure and GCP).

Week 4 ~ July 2 - July 8

Learners will develop a video indexing service using functions using AWS Lambda, Rekognition, and CloudSearch on AWS.

Week 5 ~ July 9 - July 15

learners will build a social network timeline using heterogeneous back-end storage systems. The project will cover several storage systems, including low-latency KV stores, NoSQL databases, and in-memory databases (examples include Google BigTable, Cloud SQL, MongoDB and others on GCP).

Week 6 ~ July 16 - July 22

Learners will also be introduced to iterative programming models by implementing a social graph analysis algorithm using Apache Spark on Azure.