Geospatial Data Science

Geospatial Data Science or analysis is an intensive training that will guide you through the process of using location-based information. From beginner concepts to advanced techniques, you will receive sound training on exploring geo data using Python programming language. This hands-on training equips you with the tools to unlock valuable insights from maps and spatial data, empowering you to tackle real-world challenges across various domains using spatial data.

What you will Gain from the Geospatial Data Science:

  • ● Supportive and innovative teaching environment
  • ● Extra support session weekly
  • ● Practical teaching from resourceful and internationally trained instructors
  • ● Solid Project portfolio
  • ● Employability skills
  • ● Job coaching and vacancies newsletter for job seekers
  • ● Webinars with International Speakers.

Course Outlines (Python-Based)

Introduction to Geospatial Data Analysis
Overview of Geospatial Data
Definition and characteristics of geospatial data
Getting Started with Python for Geospatial Data Analysis
Introduction to Python programming language
Setting up the development environment
Foundational python (variables, data types, logical operators, control structures, functions)
Introduction to key Python libraries for geospatial data analysis (Pandas, numpy, Geopandas, Shapely, Fiona, Matplotlib, Seaborn, Rasterio, PyProj, Folium)
Data Acquisition and Management
Importing geospatial data formats (Shapefiles, GeoTIFF, etc.)
Data manipulation and transformation using GeoPandas and other libraries
Cleaning and preprocessing geospatial data
Spatial Analysis Techniques
Spatial querying and selection
Spatial joins and overlays
Spatial operations (buffering, clipping, intersection, etc.)
Spatial statistics and analysis (e.g., spatial autocorrelation, hotspot analysis)
Geospatial Data Visualization
Introduction to data visualization principles
Plotting geospatial data using Matplotlib and Seaborn
Creating interactive maps with Folium or Plotly
Advanced Topics in Geospatial Data Analysis
Introduction to remote sensing data analysis
Introduction to spatial machine learning techniques
Introduction to web mapping and geospatial web services
Group projects or capstone projects applying geospatial data analysis techniques
Assessment and Evaluation

Program Duration: 2 Months.

Schedule: 3 Classes per Week (Option of Face to Face or Online Training Available).

PLEASE NOTE: Face-to-Face Training is ONLY available in Abuja.

Face-to-Face Training Time: 10:00 am – 3 pm (Tuesday, Friday, and Saturday every Week).

Online Training Time: 8:00 pm – 10:00 pm (Thursday, Friday, and Saturday every Week)

Note: No prior coding experience is required as we provide training from the ground up. Similarly, no prior knowledge of Geospatial analysis is necessary.

Face-to-Face Course Fee (Training Only Available in Abuja, Nigeria): N200,000 (Pay in 2 Instalments, the first payment is N150,000). Sorry, your application will not be considered if you can’t pay your training fee.

Online Course Fee (Live Instructor, open to international trainees also): N200,000 (Pay in 2 Instalments, the first payment is N150,000). Sorry, your application will not be considered if you can’t pay your training fee.

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(REGISTRATION WILL OPEN EARLY 2025)

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