Building Interactive Map for Geospatial Analysis in R

Online Data Science Series

  • Schedule

    8 – 11 September 2020 (4 Days)

    18.30 – 21.30 (3 hours / day)

  • Online-Interactive Learning

    Via Zoom

  • Investment

    IDR 550.000

Course Summary

This 4-day online workshop is a beginner-friendly introduction to visualizing geospatial data using R. By learning how to work with spatial datasets and vector, you can create a data-driven approach for your business.

Throughout the online course, we will provide participants with rich interactive experience. One Instructor and two Teaching Assistants will help participants troubleshoot or help with any difficulties encountered by participants.

NOTES: This workshop will be delivered in Bahasa Indonesia.


Upon completion of this workshop, you will be able to:

  • Work with the R language and open source packages for data cleansing and manipulation process.
  • Work with geospatial data and perform a visual exploratory and explanatory analysis.
  • Build an analysis dashboard using R reporting tools to communicate business insights.


This is an optional material that will be delivered on the first day of the workshop. You can skip the first day if you have strong R programming basics. What you will learn on the first day:

  • R and R Studio.
  • Basic data types and structure.
  • Working with lists and tabular data.
  • Data wrangling in R.
  • Retrieving Indonesia’s spatial vector from an open-source provider.
  • Working with the spatial polygon in R.
  • The grammar of graphics for geospatial data using `ggplot2`.
  • Enhancing map plots for richer visualization.
  • Using `leaflet` – a JavaScript API for creating interactive maps.
  • Adding markers and colors in `leaflet`.
  • Building various geospatial analysis graphics: Heatmap, Choropleth, and Connection Map.
  • Explore various publication options using `rmarkdown` versatile output.
  • Create a compelling and easy-to-build dashboard using `flexdashboard` package.
  • Apply your geospatial analysis for various industries.


This testimonial video is taken after our previous Online Data Science Series: Time Series Analysis for Business Forecasting.


Your Instructor

Tresna Tanesya is a Senior Data Science Instructor at Algoritma Data Science School, she has exceptional skills in extracting insights from data and using data visualization to communicate ideas. Tanesya has more than 1.000 hours of teaching experience and involved in numerous consultative data science training for our clients, to name a few:

  • Bank Central Asia
  • PT. Sigma Metrasys Solution
  • PT. Sigma Cipta Caraka
  • Tokopedia
  • Yogya Group

Online Data Science Series

Workshops in our Online Data Science Series are tailored to casual learners, working professionals, and non-programmers that are taking their first steps into data science and machine learning.

Students are not assumed to have a working knowledge of R or prior proficiency in statistics/mathematics/algebra. At such the workshop follows a gentle learning curve and emphasize on hands-on, one-to-one tutoring from our team of instructors and teaching assistants

Frequently Asked Questions

Yes, you can still attend the workshop as it is a beginner-friendly workshop.

Our system will send you an email containing a link and details to join a Google Classroom.

Online learning will be conducted via Zoom.us, Link to join the Zoom Class will be announced via Google Classroom.

Learning materials can be obtain via Google Classroom

Yes, you will receive a certificate of completion.

Workshop Receivables:

  • Workshop Lecturer’s Notes

    Including 2x Course Books (PDF), HTML files, course transcripts (if any).

  • Highly-accelerated Learning

    Learn under the assistance of the mentorship of our lead instructor and a band of qualified teaching assistants throughout the 4-day course.


    Show current and prospective employers that you’ve completed the course with a signed certificate of completion.

  • Supplement Materials

    Receive supplement datasets to practice on, reference notes, working files (R Notebook or Jupyter Notebook), and other materials that will help you master the topics.