Magellan: Geospatial Analytics on Spark Training Course

This instructor-led, live training in Uruguay (online or onsite) is aimed at field ecologists and conservation managers who wish to create data spatial projects in ArcGIS.

By the end of this training, participants will be able to:

• Output spatial data as visualizations.
• Conduct geostatics on actual data.
• Implement spatial data analysis, data processing, and mapping with ArcGIS.
• Analyze spatial data for projects in ArcGIS.

This instructor-led, live training in Uruguay (online or onsite) is aimed at intermediate-level environmental scientists and archaeologists who wish to learn how to use ArcMap in ArcGIS for collecting, organizing, managing, and analyzing geographic information.

By the end of this training, participants will be able to:

• Understand the fundamentals of ArcMap and ArcGIS.
• Collect, organize, manage, and analyze geographic information on the social and archaeological elements.
• Conduct spatial queries for impact evaluation.

By the end of this training, participants will be able to:

• Understanding GIS concepts and spatial data types using the latest version of ArcGIS Pro.
• Investigate the user interface and evaluate the uses
• Explore ArcGIS* Pro and how to utilize online content
• Manage, manipulate and analyze your own data
• Display and share your data in a meaningful and creative way

Note: We will use the latest version of ArcGIS Pro.

This instructor-led, live training in Uruguay (online or onsite) is aimed at GIS analysts who wish to automate repetitive tasks in GIS processes.

By the end of this training, participants will be able to:

• Build GIS applications using Python and ArcGIS tools.
• Develop with the ArcGIS package ArcPy, using Python.
• Apply the ArcGIS modules for map automation using object classes in Python.

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.

This instructor-led, live training in Uruguay (online or onsite) is aimed at field ecologists and conservation managers who wish to post-process Pix4D drone data.

By the end of this training, participants will be able to:

• Implement Google Earth to enhance UAV mapping .
• Use outputs of images to generate reports.
• Post-process with GIS and CAD software for advanced drone data modeling.

This instructor-led, live training in Uruguay (online or onsite) is aimed at field ecologists and conservation managers who wish to land survey and drone map with Pix4D.

By the end of this training, participants will be able to:

• Use end to end drone mapping processes and techniques.
• Achieve high surveying accuracy.
• Understand the fundamentals of global coordinate systems and GPS.
• Generate and analyze survey output with Pix4D's image processing software.

This instructor-led, live training in Uruguay (online or onsite) is aimed at intermediate-level geographers who wish to deepen their expertise in spatial analysis, data management, and GIS applications.

By the end of this training, participants will be able to:

• Apply advanced spatial analysis techniques to solve complex geographical problems.
• Manage large spatial databases and perform data quality control.
• Create dynamic and interactive maps and visualizations for various applications.
• Utilize programming and automation to streamline GIS workflows.

This instructor-led, live training in Uruguay (online or onsite) is aimed at developers who wish to enhance their website or web application by adding geo-location functionality through Google Maps.

By the end of this training, participants will be able to:

• Embed a map into a new or existing website or web application.
• Display live data that synchs with current location.
• Create a mashup that includes Google Maps.
• Apply good CSS and JavaScript coding practices
• Create a custom map for an application.

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.

The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers.

This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.

In this instructor-led, live training in Uruguay, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.

By the end of this training, participants will be able to:

• Learn how to use Spark with Python to analyze Big Data.
• Work on exercises that mimic real world cases.
• Use different tools and techniques for big data analysis using PySpark.

In this instructor-led, live training in Uruguay, participants will learn about the technology offerings and implementation approaches for processing graph data. The aim is to identify real-world objects, their characteristics and relationships, then model these relationships and process them as data using a Graph Computing (also known as Graph Analytics) approach. We start with a broad overview and narrow in on specific tools as we step through a series of case studies, hands-on exercises and live deployments.

By the end of this training, participants will be able to:

• Understand how graph data is persisted and traversed.
• Select the best framework for a given task (from graph databases to batch processing frameworks.)
• Implement Hadoop, Spark, GraphX and Pregel to carry out graph computing across many machines in parallel.
• View real-world big data problems in terms of graphs, processes and traversals.

This course is aimed at developers and data scientists who wish to understand and implement AI within their applications. Special focus is given to Data Analysis, Distributed AI and NLP.

MLlib is Spark’s machine learning (ML) library. Its goal is to make practical machine learning scalable and easy. It consists of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as lower-level optimization primitives and higher-level pipeline APIs.

It divides into two packages:

• spark.mllib contains the original API built on top of RDDs.

• spark.ml provides higher-level API built on top of DataFrames for constructing ML pipelines.

Audience

This course is directed at engineers and developers seeking to utilize a built in Machine Library for Apache Spark