Development Environment in Data Science

Data Science
Engineering and development
Open Source
On-site courses
Remote/Virtual
Face-to-face
English
French

Objectives

Understand the data science ecosystem and know the tools related to the realization of a data science project.

Prerequisites

Comfortable with computer tools, have an internet connection

Learning and technical resources:

  • Dedicated digital training platform (LMS).
  • Sessions with the trainer, training material in digital format, balance between theory and pratice.

Assesment:

Practical application and exercises, evaluation questionnaire

Results & skills expected at the end of the training:

At the end of this training, the participant will have a clear idea of what data science is, the tools available to implement data science projects, which programming language to choose and how to organize their work.

Program

Detailed training program

DAY 1

  • The unix environment, interacting with a shell, open source tools (sed, awk, grep, jq, csvkit, etc.), R and Python, SQL and NoSQL
  • Revision control and collaborative work with Git
  • The methodology for managing a data science project
  • Software engineering fundamentals and best practices

DAY 2

  • Information gathering and processing (experimental designs and clinical trials, surveys and polls, web data, open data)
  • Distributed architecture and database, map-reduce, big data, Apache Spark

 

Duration
14 hours
Level
Beginner
Audience
Anyone who wants to discover the data science ecosystem.
Participants
8 people maximum
Nous consulter pour un devis personnalisé.

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