Fiches de cours

Lab in data science

COM-490

Enseignant(s) :

Bouillet Eric Pierre
Delgado Borda Pamela Isabel
Sarni Sofiane
Verscheure Olivier

Langue:

English

Withdrawal

It is not allowed to withdraw from this subject after the registration deadline.

Summary

This hands-on course teaches the tools & methods used by data scientists, from researching solutions to scaling up prototypes to Spark clusters. It exposes the students to the entire data science pipeline, from data acquisition to extracting valuable insights applied to real-world problems.

Content

1. Crash-course in Python for data scientists

2. Distributed data wrangling at scale

3. Distributed processing with Apache Spark

4. Real-time big data processing using Apache Spark Streaming

5. Final project - Summing it all up

Keywords

Data Science, IoT, Machine Learning, Predictive Modeling, Big Data, Stream Processing, Apache Spark, Hadoop, Large-Scale Data Analysis

Learning Prerequisites

Required courses

Students must have prior experience with Python

Recommended courses

Students must have prior experience with at least one general-purpose programming language.

Important concepts to start the course

It is recommended that students familiarize themselves with concepts in statistics and standard methods in
machine learning.

Learning Outcomes

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

Transversal skills

Teaching methods

... using real-world datasets and Cloud Compute & Storage Services

Expected student activities

Assessment methods

Supervision

Office hours Yes
Assistants Yes
Forum Yes

Resources

Virtual desktop infrastructure (VDI)

No

Bibliography


A list of additional readings will be distributed at the beginning of the course

Ressources en bibliothèque
Websites

Dans les plans d'études

Semaine de référence

 LuMaMeJeVe
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     
En construction
 
      Cours
      Exercice, TP
      Projet, autre

légende

  • Semestre d'automne
  • Session d'hiver
  • Semestre de printemps
  • Session d'été
  • Cours en français
  • Cours en anglais
  • Cours en allemand