Spatial Computational Thinking Professional Certificate

Professional Certificate in

Spatial Computational Thinking

NUS

What you will learn

Writing procedural algorithms for generating spatial information models using fundamental data structures and control-flow constructs.
Integrating multiple procedures to generate complex spatial information models capturing various relationships and constraints.
Evaluating alternative spatial information models to support performance-based decision making.

Spatial Computational Thinking is increasingly being recognised as a fundamental skill for various spatial disciplines. It involves idea formulation, algorithm development, solution exploration, with a focus on the manipulation of geometric and semantic datasets. In this Professional Certificate Program, you will learn the theoretical knowledge and practical skills required for leveraging computation for the manipulation of various types of spatial data.

The program consists of three courses, starting with the fundamentals and gradually increase in complexity.

The first course – Procedural Modelling – focuses on the fundamentals of procedural programming for generating spatial models. You will learn how to code, using functions, data structures and control-flow statements. You will write procedures for generating geometric models with attribute data. By the end of the course, you will be able to write your own procedures for generating spatial information models.
The second course – Generative Modelling – focuses on generating spatial information models capturing various relationships and constraints. You will learn a set of geometric modelling concepts for generating spatial models. You will create multiple procedures that annotate and query your models using attribute data. By the end of the course, you will be able to create your own scripts consisting of multiple procedures working together to generate complex spatial information models.
The third course – Performative Modelling – focuses on evaluating alternative spatial models to support evidence-based decision making. You will learn methods for calculating various spatial performance metrics related to the built environment. You will use these performance metrics to carry out comparative analysis of design options. By the end of the course, you will be able to create scripts that automate the process of generating and analysing alternative design options.

All the courses will use a free browser-based software to write algorithms for generating and visualizing 3D models, called Möbius Modeller. The programming language uses a visual programming approach combining flowcharts with procedural programming. This will allow you to quickly learn the knowledge and skills required for writing complex computational procedures for generating, analysing, and visualizing complex 3D spatial information models. The programming knowledge you gain will be highly transferable if you later choose to use other languages such as JavaScript, Python, Java, and PHP.

Expert instruction

3 skill-building courses

Self-paced

Progress at your own speed

4 months

4 - 6 hours per week

$447

USD

For the full program experience

Courses in this program

NUS's Spatial Computational Thinking Professional Certificate
4–6 hours per week, for 5 weeks
This course will focus on the fundamentals of procedural programming for generating spatial models. You will learn how to code, using functions, data structures and control-flow statements. You will create procedures to generate geometric models with attribute data. By the end of the course, you will be able to write your own procedures for generating spatial information models.
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4–6 hours per week, for 5 weeks
This course focuses on generating spatial information models capturing various relationships and constraints. You will learn a set of advanced modelling techniques for generating spatial models. You will create multiple procedures that annotate and query your models using attribute data. By the end of the course, you will be able to create your own scripts consisting of multiple procedures working together to generate complex spatial information models.
View the course
4–6 hours per week, for 5 weeks
This course focuses on evaluating alternative spatial models to support evidence-based decision making. You will learn methods for calculating various spatial performance metrics related to the built environment. You will use these performance metrics to carry out comparative analysis of design options. By the end of the course, you will be able to create scripts that automate the process of generating and analysing alternative design options.
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- The growth in importance of skills such as technology design and programming highlights the increasing demand for various forms of technology competency (World Economic Forum, 2018).
- By 2030, demand for skilled workers will outstrip supply, resulting in the global talent shortage of more than 85.2 million people (Korn Ferry, 2018).
- A shortage of digital talent is hampering the digital transformation of over 54% of the organisations surveyed (Capgemini and LinkedIn, 2017).
- Computational thinking is used to develop 21st-century skills such as logical thinking and problem-solving skills among students. (European Commission, Joint Research Centre, 2016).

Meet your instructor
from The National University of Singapore (NUS)

Patrick Janssen

Associate Professor

National University of Singapore

Experts from NUS committed to teaching online learning

FAQs

The only software you need is a recent version of any Chromium-based web browser (such as Google Chrome, Microsoft Edge, Opera, or Brave). During the program, we will use a free and open-source software app called Möbius Modeller. Even after completing the program, you will be able to continue using this app for free.
You do not need any specialized hardware to complete the exercises in the program. A recent mid-range laptop will be sufficient. A laptop with a dedicated graphics card will result in a smoother user experience.
No, this program is designed for beginners and we will step you through all the programming required.
Yes. You will learn procedural programming, using typical imperative programming-language constructs. You will also learn how to create computational procedures for manipulating spatial data in diverse ways.
Yes. The models that you create (either during the program or after) can be shared either by exporting the models in other formats or by publishing them on the internet as interactive web pages. Publishing a model is straightforward and is one of the techniques that you will learn.
You will learn the fundamental concepts of programming, such as variables, data types, control flow, data structures and functions. Although we will not specifically teach languages such as JavaScript, Python, etc, the fundamental concepts that you learn will be transferable to all these languages.
No, you need an average grade for all assignments of 70%. This means you can do poorly or miss an assignment as long as you do well enough on other assignments to achieve 70% overall.
Most of your computational modelling assignments will be graded using an automated online grader. For each assignment, you will be given specific instructions on the model that you need to create. You will upload your answer model, and within a few seconds, you will receive the result, with feedback. If the model you uploaded is not correct, you will have multiple chances to try again. For the last assignment of the course, you will be required to create your own model from scratch. This final assignment will be manually graded.
An overall average for all assignments of 70% is required to pass the course.

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