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. 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 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.