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Computational Reasoning with Microsoft Excel

National University of Singapore via edX


Through a series of fun and engaging hands-on activities in Microsoft Excel, this module aims to equip the learner with the ability to thoughtfully apply computational tools when solving complex real-world problems. This module aims to impart to the learner fundamental skills in Microsoft Excel for dealing with large amounts of data, and the ability to critically self-evaluate the way they apply these skills. They will learn to identify problems and design solutions, while also developing a critical awareness of the merits and limits of their methods, thereby empowering them to make better-informed decisions and to reason effectively in a variety of contexts.


Lesson 1: Introduction to Computational Reasoning

  • Understand the computational problem-solving process, and able to clearly define objectives to solve problems.
  • Understand the obstacles that make it difficult to develop good computational solutions

Lesson 2: What’s Going On and Why? Understanding the Situation and Identifying Problems Using Data Analysis

  • Effectively use the various tools of Microsoft Excel to analyse data.
  • Identify patterns or breaks in patterns to better understand and describe what is going on in the dataset, and to identify possible causes to problems.
  • Distinguish between direct and proxy measures, with the awareness of the problems inherent in using proxy measures.

Lesson 3: How to Effectively Reason with Data

  • Identify assumptions underlying proxy measures and evaluate the strength of these assumptions.
  • Formulate clear and unambiguous hypotheses based on data and evaluate the strengths of these hypotheses.

Lesson 4: Anyone Can Model: The Fundamentals of Modelling

  • Read and comprehend conditionals and nested conditionals in order to organise and sort data on a large scale
  • Create accurate classification models based on the processes of pattern recognition and abstraction.
  • Appreciate the difficulties in developing abstract models, and identify shortcomings of such models.

Lesson 5: Social Network Analysis: What’s Going on in the Neighbourhood?

  • Develop a firm understanding of the concepts of loops and nested loops
  • Develop a nuanced understanding of the notion of “importance” in a social network through the concepts of degree centrality and betweenness centrality.

Lesson 6: Greedy Methods: How to Solve Problems in a Fast and Systematic Manner

  • Articulate Greedy Rules when attempting to solve problems via the optimisation-approach.
  • Evaluate different Greedy Rules to prescribe effective solutions

Lesson 7: A Fun Introduction to Coding with VBA

  • Basic knowledge of VBA to automatically navigate around a spreadsheet and manipulate cells and data.
  • Apply conditionals in VBA to process rows of information and generate output.
  • Competently debug errors in VBA.

Lesson 8: Let’s Up Our VBA Game!

  • Apply loops in VBA to process rows of information and generate output.
  • Formulate precise conditionals through the exercise of pattern recognition to solve more complex problems.

Taught by

Jonathan Sim


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