Project

Project info page

Project info slides


Lectures

Lecture 01 - Intro to ADA

Lecture 02 - Handling Data

Lecture 03 - V for Variety

Lecture 04 - Data Visualization

Lecture 05 - Read the Stats Carefully

Lecture 06 - Scaling up

Lecture 07 - Observational Studies

Lecture 08 - Supervised Learning

Lecture 09 - Applied Machine Learning

Lecture 10 - Unsupervised Learning

Lecture 11 - Handling Text

Lecture 12 - Handling Networks


Tutorials and Homeworks

Tutorials on Github
Tutorial 0
Tutorial: Data From The Web
Tutorial: Data Stories


Tentative lecture schedule

Week Date of Monday Lecture Lab Session
1 2018-09-17 Intro Intro to tools
2 2018-09-24 Handling data Pandas
3 2018-10-01 V for variety Talk: Claudiu Musat (Swisscom)
4 2018-10-08 Visualization Visualization, Data cluedo
5 2018-10-15 Read the stats carefully Cluster, Projects
6 2018-10-22 Scaling up Spark, Good code practices
7 2018-10-29 Observational studies Web scraping, Data stories
8 2018-11-05 Supervised learning Applied machine learning
9 2018-11-12 Applied ML Talk: Teo Stocco (Smood.ch)
10 2018-11-19 Unsupervised learning Talk: Ryan Faulkner (Deepmind)
11 2018-11-26 Handling text Primer on Networks
12 2018-12-03 Handling text Primer on Text
13 2018-12-10 Handling networks Talk: Christian Sinobas (KiWi)
14 2018-12-17 ADA in action TBD


Contact

The main channel for class-related communication is Mattermost.

Mattermost server: https://icmattermost.epfl.ch/cs-401/

Instructor

Robert West @west

TAs

Tiziano Piccardi @tiziano
Jérémie Rappaz @jay
Panayiotis Smeros @psmeros
Kristina Gligorić @kristina
Ramtin Yazdanian @ramtin
Periklis Chrysogelos @periklis
Panagiotis Sioulas @psiou
Tugrulcan Elmas @teajay

AEs

Nuno Gonçalves @nunomota
Léonore Guillain @leonore_guillain
Armand Boschin @armand
Ali Ben Lalah @aliben
Samuel Beuret @beuret
Quentin Bacuet @quentin_bacuet
Quentin Rebjock @sappy
Pierre-Alexandre Lee @palex
Isabela Constantin @isabelaconstantin


Resources