darkdrei / assignments-2017

Labs assignments

Practical assignments

Tell me and I forget. Teach me and I remember. Involve me and I learn.

Benjamin Franklin

There will be two kinds of assignments: 5 Labs and one project. Pre-lab homework will be assigned for some labs. Students are expected to complete and submit the assigned pre-lab homework before each lab session.

Labs

The students will begin by creating a basic toolbox to get started in the Cloud. This will prepare them to practice with APIs, the doors in the Cloud. Together, these things will allow the students to mine the deluge of data coming from the Cloud, or use new advanced analytics services provided nowadays by the Cloud. Finally, we will look under the hood of these advanced analytics services in the Cloud, either in terms of software or hardware, in order to understand how their high performance requirements can be provided. The purpose is to provide code examples that can get you started easily.

( WARNING: Under revision the content of this github)

• Lab 1: Basic "Knowledge Toolbox" to getting started in the Cloud
• Lab 2: Doors in the Cloud and Extracting and Analyzing data from the Cloud
• Lab 3: Interacting with users and services in the Cloud
• Lab 4: Under the hood of Cloud Advanced Analytics Services
• Lab 5: Extracting and Analyzing data using Elastic Search and Kibana

Course Project

The project can be done in groups of 1,2 or 3 students. The project need to be approved by your teacher before starting (from the student's proposal for the project).

Six levels:

• Minimum (max grade obtained 60%): One possibility of project is to prepare a presentation of some related technologies with this part of the course (with slides).

• Medium (max grade obtained 90%): Another alternative to the project may be to create a self-contained practical guide (hands-on) that guides the reader in learning one of the latest cloud technologies.

• Full (option 1): The standard project is to create an application using existing APIs. Starting here for more information. For example:

  • Colorize photos using Deep Learning with Algorithmia API
  • Building a ChatBot with Watson API
  • News Aggregator based on Sentiment with Aylien API

• Full (option 2): Carry out one of the projects suggested by the professor during this course.

• Advanced (option 1) (bonus of +10%) The project offers an excellent opportunity for the student to dive into course content by implementing a protoype (proof of concept implementation of a business idea created by the student) using the latest Cloud technology. Your teacher will be deligted to help you

• Advanced (option 2) (bonus of +10%) Surprise the teacher with a project proposal that he accepts

Deadlines

Deadlines for Labs

The deadlines indicated are suggestions for when you should ideally finish each Hands-on. They are meant to help keep you on track so that you maintain an appropriate pace throughout the program. There are penalties if you miss these deadlines. It is a recommended best practice to try and meet each suggested deadline.

Deadline for course Project

The deadlines indicated in the course syllabus is a hard deadline.

Acknowledgements

I would like to thank some of my former students for his help with proofreading this documentation and improving it: Eloy Gil, Dani Cea, Francesc Sastre, Maurici Yagües and Mauro Gómez. Also to Barcelona Supercomputing Center for give acces their computing facilities to our students.