Coursebooks 2017-2018

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Systems for data science

CS-449

Lecturer(s) :

Koch Christoph

Language:

English

Summary

The course covers fundamental principles for understanding and building systems for managing and analyzing large amounts of data.

Content

 

Programming methods, including parallel programming:

Big data systems design and implementation:

Changing data:

Online / Streaming / Real-time analytics:

Keywords

Databases, data-parallel programming, NoSQL systems, query processing.

Learning Prerequisites

Required courses

CS-322: Introduction to database systems

Recommended courses

CS-323: Introduction to operating systems

CS-206 Parallelism and concurrency

Important concepts to start the course

 

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

Ex cathedra; including exercises in class, practice with pen and paper or with a computer, and a project

Expected student activities

During the semester, the students are expected to:

Assessment methods

Homeworks, written examinations, project. Continuous control

Supervision

Office hours Yes
Assistants Yes
Forum Yes
Others Office ours by appointment

Resources

Bibliography

Relevant resources (textbook chapters, articles, and videos) posted on moodle page.

In the programs

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
Under construction
 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German