Python for Geographic Information System (GIS) Training Course

This instructor-led, live training in Taiwan (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 Taiwan (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 Taiwan (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 Taiwan (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

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

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

This instructor-led, live training in Taiwan (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.

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

• Set up the necessary environment to start developing Pandas workflows at scale with Modin.
• Understand the features, architecture, and advantages of Modin.
• Know the differences between Modin, Dask, and Ray.
• Perform Pandas operations faster with Modin.
• Implement the entire Pandas API and functions.

This instructor-led, live training in Taiwan (online or onsite) is aimed at data scientists who wish to use Pandas to preform predictive analysis with machine learning.

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

• Perform data wrangling in Python.
• Conduct ETL operations for machine learning.
• Create data visualizations with Pandas

This instructor-led, live training in Taiwan (online or onsite) is aimed at data scientists and software engineers who wish to use Dask with the Python ecosystem to build, scale, and analyze large datasets.

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

• Set up the environment to start building big data processing with Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask.
• Understand how Dask accelerates parallel computing in Python.
• Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to maintain high performance in handling large datasets.

This instructor-led, live training in (online or onsite) is aimed at developers who wish to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

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

• Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
• Understand the key concepts, features, and benefits of the FARM stack.
• Learn how to build REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (front end and back end) using the FARM stack.

This instructor-led, live training in Taiwan (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier using the FastAPI library.
• Learn how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Taiwan (online or onsite) is aimed at developers who wish to use SciPy to create advanced scientific computing functions with Python.

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

• Set up the necessary development environment to start creating scientific computing functions.
• Get the full benefit of SciPy features by performing practical examples of complex operations.
• Implement and optimize mathematical algorithms and functions to solve scientific problems.
• Design data structures and interpolation methods for visualization, processing, and analysis.

This instructor-led, live training in Taiwan (online or onsite) is aimed at developers who wish to use PyGame to create and build games using Python programming.

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

• Set up the necessary development environment to start creating game applications with PyGame and Python.
• Learn how to create interactive PyGame applications integrated with animations and multimedia features.
• Run and test game programs with PyGame test suite and convert them into executable files.

This practical course is addressed to Python developers that want to create and maintain their first web applications. It is also addressed to people who are already familiar with other web frameworks such as Django or Web2py, and want to learn how using a microframework (i.e. a framework which glues together third-party libraries instead of providing a self-contained universal solution) changes the process.

A significant part of the course is devoted not to Flask itself (it's tiny), but to third-party libraries and tools often used in Flask projects.

This instructor-led, live training in Taiwan (online or onsite) is aimed at developers who wish to use the advanced features of Flask to build scalable web applications on top of MongoDB.

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

• Set up the necessary development environment to start developing web applications with Flask.
• Get to know the advanced concepts and techniques for real-world Flask projects.
• Build a RESTful API server on top of MongoDB.
• Learn how to containerize, test, and deploy microservices with Flask, Docker, and Amazon EC2.
• Gain some insights on the advanced Flask integrations for scaling web applications.