cloud computing course (cc-mei)

Cloud Computing for Artificial Intelligence 2023 (CC-MEI)

Master Ingeniería Informática (FIB/UPC – 2023)

Oficial web site

El idioma de impartición de las clases en esta edición del curso será en español/català y toda la documentación será en inglés. El curso empezará el lunes 13/02/2023.

 

Course Goal:

Services converge and pass from the physical world to the digital world, making them accessible from any electronic device. Cloud Computing is what makes it possible for digital technology to penetrate every corner of our economy and society. This course aims to help students understand this profound transformation that is causing Cloud Computing and related emerging technologies such as Artificial Intelligence. This course will encourage their desire to want to delve further into this exciting world of technology and become actively involved.

Course Description:

This course will review Cloud Computing technologies that will shape our near future, as well as attempt to visualize in which direction this technology will take us. This edition of the course will pay special attention to the relation of Cloud Computing with Artificial Intelligence in general and Deep Learning in particular.  We will look under the hood of these advanced analytics services in the Cloud, either in terms of software or hardware, to understand how their high-performance requirements can be provided.

The practical component is an important part of this subject. In this course, the “learn by doing” method is used, with a Hands-on set that the students must carry out throughout the course. The course will be marked by a continuous assessment which ensures constant and steady work. The course is also based on reading and presenting related topics.

Course workload: important warning

The student should be aware that CC-MEI 2022 edition is a 3.0 ECTS course that requires an effort from the student equivalent to 75 hours (3.0 ECTS*25 hours/ECTS).  This means more than 10 hours per week(4 hours in class + 6 hours outside of class on average). It is not recommended to take this course if the student has other commitments during the term, preventing them from dedicating the required amount of hours to this course. They can wait for the next course edition.

 

Course Content:

0. Motivation

1. Cloud Computing paradigm

2. Cloud Computing technologies

3. New relate paradigms

4. Currents Cloud Computing software stack and computer hardware

5. The next wave of Cloud: Programming AI & Scaling AI applications

Course Activities:

  • Class attendance and participation: Regular attendance is expected, and is required to be able to discuss concepts that will be covered during class. 

  • Hands-on: Some exercises will be conducted as hands-on sessions during the course using supercomputing facilities. The student’s own laptop will be required to access these resources during the theory class. Each hands-on session will involve writing a lab report with all the results. There are no days for theory classes and days for laboratory classes. Theoretical and practical activities will be interspersed during the same session to facilitate the learning process.
  • Homework Assignments: Homework will be assigned weekly that includes reading the documentation that expands the concepts introduced during lectures, and periodically will include reading papers related to the lecture of the week and prepare presentations (with slides).  Some students randomly chosen will present their presentation.
  • Assessment: There will be 2 short midterms (45-55 minutes) exams along the course. The student is allowed to use any type of documentation (also digital via the student’s laptop).
  • Student presentation: Students randomly chosen will present the homework (presentations/projects).

Grading Procedure:

The evaluation of this course can be obtained by continuous evaluation. This evaluation will take into account different items:

  • In-class exams will account for  10% of the grade:
    • Midterm 1: 5%
    • Midterm 2: 5%
  • Attendance (& participation in class ) will account for 14% of the grade
  • Homework, reading papers, and presentations will account for 25% of the grade:
    • Presentation 1: 13%
    • Presentation 2: 2%
    • Presentation 3: 5%
    • Presentation 4: 5%
  • Hands-on (+reports) will account for 51% of the grade:
    • Hands-on 1: 5%
    • Hands-on 2: 2%
    • Hands-on 3: 12%
    • Hands-on 4: 2%
    • Hands-on 5: 15%
    • Hands-on 6: 15%

Requirements for continuous evaluation: 

  • Minimum of 80% of attendance in-class sessions
  • Minimum of 60% of Homework and presentations
  • Minimum of 60% of Hands-on

Course Exam, for those students who have not benefited from the continuous evaluation, will be announced during the course. This exam includes the evaluation of the knowledge of the entire course (practical part, theoretical part, and self-learning part of homework). During this exam, the student is not allowed to use any type of documentation (neither on paper nor digital).

Previous Knowledge:

Python is the programming language of choice for the labs’ sessions of this course. It is assumed that the student has a basic knowledge of Python prior to starting classes. Also, some experience with Linux basics will be necessary.

Documentation:

Class handouts and materials associated with this class can be found on the Racó-FIB web server.

Profesor 

Jordi Torres Viñals
Email: torres‘.@xupc.edu
Web: https://jorditorres.ai
Twitter: @JordiTorresAI
Office: UPC Campus Nord, Modul C6. Room 217. Jordi Girona 1-3, 08034 – Barcelona

This syllabus will be revised/updated until the start of the course (last modified 12/02/2023)

Banner picture: CC-MEI 2018 students.