Les formations Spatial analysis
L'analyse spatiale (également appelée statistiques spatiales, analyse spatiale, analyse géospatiale, analyse géospatiale, analyse géospatiale et analyse géospatiale) fait référence à l'application de l'analyse statistique et d'autres techniques analytiques à des données ayant un aspect géographique ou spatial. Une telle analyse utilise généralement un logiciel capable de rendre des cartes, de traiter des données spatiales et d'appliquer des méthodes analytiques à des ensembles de données terrestres ou géographiques, y compris l'utilisation de systèmes d'information géographique et de géomatique.
Plan des Formations
| Code | Nom | Durée | Aperçu |
|---|---|---|---|
| magellan | Magellan: Geospatial Analytics on Spark | 14 heures | Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics. This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark. By the end of this training, participants will be able to: Efficiently query, parse and join geospatial datasets at scale Implement geospatial data in business intelligence and predictive analytics applications Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables Audience Application developers Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| deckgl | deck.gl: Visualizing Large-scale Geospatial Data | 14 heures | deck.gl is an open-source, WebGL-powered library for exploring and visualizing data assets at scale. Created by Uber, it is especially useful for gaining insights from geospatial data sources, such as data on maps. This instructor-led, live training introduces the concepts and functionality behind deck.gl and walks participants through the set up of a demonstration project. By the end of this training, participants will be able to: Take data from very large collections and turn it into compelling visual representations Visualize data collected from transportation and journey-related use cases, such as pick-up and drop-off experiences, network traffic, etc. Apply layering techniques to geospatial data to depict changes in data over time Integrate deck.gl with React (for Reactive programming) and Mapbox GL (for visualizations on Mapbox based maps). Understand and explore other use cases for deck.gl, including visualizing points collected from a 3D indoor scan, visualizing machine learning models in order to optimize their algorithms, etc. Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice |
| qgis | QGIS for Geographic Information System | 21 heures | A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics. QGIS functions as geographic information system (GIS) software, allowing users to analyze and edit spatial information, in addition to composing and exporting graphical maps. QGIS supports both raster and vector layers; vector data is stored as either point, line, or polygon features. Multiple formats of raster images are supported, and the software can georeference images. To summarize it allows the users to Create, edit, visualise, analyse and publish geospatial information on Windows, Mac, Linux, BSD. This program, in its first phase, introduces the QGIS interface for general usage. In the second phase, we introduce PyQGIS - the python libraries of QGIS that allows the integration of GIS functionalities in your python code or your python application, so that you may even create your own Python Plugin around a particular GIS functionality. |
Upcoming Courses
| Formation | Date Formation | Prix [A distance / Classe] |
|---|---|---|
| Magellan: Geospatial Analytics on Spark - Poitiers | mar, 2018-06-12 09:30 | 3500EUR / 4100EUR |
| Magellan: Geospatial Analytics on Spark - Bordeaux, Mériadeck | mer, 2018-06-13 09:30 | 3500EUR / 4100EUR |
| QGIS for Geographic Information System - Grenoble, Centre Ville proche Gare | mer, 2018-06-13 09:30 | 5250EUR / 6050EUR |
| deck.gl: Visualizing Large-scale Geospatial Data - Limoges, Centre Ville | lun, 2018-06-18 09:30 | 3000EUR / 3600EUR |
| deck.gl: Visualizing Large-scale Geospatial Data - Amiens, Centre Ville | mer, 2018-06-20 09:30 | 3000EUR / 3600EUR |
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