Development Environment in Data ScienceHome Training Catalog 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. Prerequisite: Comfortable with IT tools, Internet connection available. Educational and technical material and resources: Sessions with the trainer Teaching aids in digital format Alternating between theory and practice Assesment: Practical application and exercises, on-the-spot assessment of training. Expected results & skills at the end of the training: At the end of this course, participants will have a clear idea of what data science is, the tools available for implementing data science projects, which programming language to choose and how to organise their work. 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 Download the full program 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. Are you looking for information about a training course? You want to set up a customized training session? Contact our pedagogical team! Notice: JavaScript is required for this content.
