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S&DE Atelier: Visual Analytics

Description

COURSE OBJECTIVES

  • Learn how to best design charts and visualizations for effective communication
  • Acquire practical experience with a number of frameworks for data analysis and visualization (Jupyter, Pandas, Bokeh, Folium, ElasticSearch, Spark, Zeppelin)
  • Create a data analysis platform in a group project

 

COURSE DESCRIPTION
The course is composed of 4 parts. In the first, we learn how human vision works and how to design charts and visualizations for effective communication. In the second part, we see how to use Jupyter, Pandas, and Bokeh to perform data cleaning, analysis, and visualization. We also cover how to deal with geo-spatial data and how to manipulate geocoded objects. In the third part, we learn how to index, query, and aggregate data at scale with ElasticSearch, and how to create interactive dashboards with Kibana and Canvas. In the last part, we see how to analyze ultra-large datasets with Apache Spark and the Zeppelin notebook, discussing how the Spark optimizer works under the hood.

 

LEARNING METHODS

Lectures, Interactive coding sessions, Hands-on tutorials, Assignments, Group project

 

EXAMINATION INFORMATION
This is an atelier course with neither midterm nor final exam. The pass/fail and the final grade are based on a number of assignments and a final project.

 

REFERENCES

  • Show me the numbers (2nd edition) - Stephen Few Open source tools and frameworks

People

 

D'Ambros M.

Course director

Additional information

Semester
Spring
Academic year
2020-2021
ECTS
6
Language
English
Education
Master of Science in Software & Data Engineering, Core course, Atélier, 1st year