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6 Best Online Spatial Data Courses & Certification of 2020

Spatial Data Courses

It is extremely difficult for students with so many Spatial Data courses to meet their needs. Learners often ask whether for each case there is a Spatial Data course. The reply is YES. Popular courses are available below. Registration for the right course is a vital factor for your career advancement. This article selected the best Spatial Data courses in 2020 by hand.

The main purpose is to illustrate each category of the best known and famous courses.

Based on your choice, choose one that best suits your needs.

However, let’s take a look at the best of the market’s Spatial Data courses.

1. Spatial Data Science and Applications by Yonsei University (Coursera)

Duration: 15 hours

Rating: 4.4 out of 5

If you know the fundamentals of data science , research and want to expand on them, then this is access to the best choices online. The classes highlighted the implications of these datasets and also how open source software addresses these ideas issues. Explore the correct areas, applications and tools. Once you get an overview of basic subjects, the mentor will guide you through each discipline and its applications.

Key Highlights:

  • Learn about Hadoop’s environment and resources.
  • Retrieve data from datasets and review more.
  • Try to test your comprehension through the quizzes.
  • Free enrolment enables you to automatically learn and the buyable option for the verified certification is available.
  • Geographical information systems, DBMS, big data systems, and tools are the topics covered.

You can Sign up Here 

2. Spatial Data with R (DataCamp)

Duration: 20 hours

Rating: 4.5 out of 5

Spatial analysis studies are one of the key methods for drawing information that is useful for socio-economic, geological decision-making and are rapidly becoming a critical aspect in different industries. If you are not familiar with this subject, this website will provide you with an overview and a fundamental understanding of this field. Start with small real-life examples, an introduction to ggmap and ggplot2, after which the lectures talk about object classes, the process of exploring them with a world map, reading data in R, and more.

Key Highlights:

  • A presentation focused on real-life situations makes it easy to understand.
  • The competence level consists of four courses.
  • Fifty-eight sessions to work with the lectures.
  • Create a raw data visualization and add credit to the map.
  • The first module is freely available.
  • Get tips and advice on polishing your charts.

You can Sign up Here

3. Core Spatial Data Analysis: Introductory GIS with R and QGIS (Udemy)

Duration: 2.5 hours                                                                                  

Rating:  4.3 out of 5

If you seem to be intimidated with working with spatial data or if you have perhaps not found the appropriate content to guide you through the practical aspects of spatial analysis, this course should be considered. The lessons encourage you to get hands on from the start and work with real-world examples, and offer insights into how such analyzes will answer questions.

Key Highlights:

  • Concrete examples illustrate every subject.
  • Initial lectures cover the required software and materials along with the lessons.
  • Show potential employers your project.
  • There are numerous tips to prevent glitches.
  • Work on R and QGIS.
  • 32 Readings + 1 Article + 4 Download tool + Sectional quizzes + Lifelong access + Completion Certificate.
  • The mentor will be there every step of the way to answer your doubts.

You can Sign up Here 

4. Spatial Data Science: The New Frontier in Analytics (Esri Academy)

Duration: 6 weeks, 2 to 3 hours per week

Rating: 4.3 out of 5

This course helps you to identify location patterns and use them to develop predictive modeling. You can not only get a deep understanding of huge bunches of information, but also work with Esri’s ArcGIS tools. In addition, you can understand how well-known open source modules are incorporated into the analytical process.

Key Highlights:

  • Pattern mining, predictive modeling, object detection and more are part of hands-on activities.
  • Basic Python awareness and statistics can be useful, but not mandatory.
  • Downloadable content that passes through tips for success and an overview of the course content is available.
  • Prepare input files for analysis with tools for visualization and engineering.
  • The course registration can be done free of charge.
  • Free access to a software suite for analyzing information and sharing findings is provided.

You can Sign up Here

5. Working with Geospatial Data in Python (DataCamp)

Duration: 4 hours                                                                                     

Rating: 4.4 out of 5

For geospatial data , various programming languages are used. This program uses libraries such as GeoPandas from Python to introduce you to the idea and terminology. You will also review the methodologies for reading, extracting and visualizing information. Recognize patterns, their relation and how they can be used in Python queries. The final class set allows you to practice with multiple datasets. See our Tutorials for Best Python Collection.

Key Highlights:

  • Theory lectures are followed by fifty-eight exercises and practice assignments.
  • The significance of and application of the reference system, together with GeoPandas, are covered.
  • Free access is available to the first section.
  • Case studies of handicrafted mining sites.
  • Apply customized operations as required.

You can Sign up Here 

6. Visualizing Geospatial Data in R (DataCamp)

This course was developed to start with the basics of spatial analysis. The lessons are divided into four parts and one by one passes through the basic concepts. Take the example of a US property market and explore how to leverage ggplot2 and ggmap to add context to your plots. The following modules discuss how to handle polygons, rasters and point data, how to improve the visual display of maps and more.

Key Highlights:

  • Look at packages such as tmap, sp, raster, to name a few.
  • Draw and manipulate data information to produce maps.
  • The first section is free to view.
  • 58 exercises are interactive classes.

Duration: 4 hours                                                                                     

Rating: 4.4 out of 5

You can Sign up Here

Wrapping Up

This is the list of the 6 Best Online Spatial Data Courses & Certification of 2020. They are popular and loved by many data science learners. You will find between these courses what you need to learn in order to continue your data science learning path.

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