Course description
Computational Reasoning with Microsoft Excel
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.
Upcoming start dates
Suitability - Who should attend?
Prerequisites:
None
Outcome / Qualification etc.
What you'll learn
- Become familiar with the process of computational problem-solving
- Simplify and analyse complex problems and identify possible solutions.
- Communicate effectively with others who engage in similar ways of problem-solving.
- Use Microsoft Excel to form persuasive arguments and prescriptions
- Basic data preparation with useful formulae
- Visualise data with Pivot tables
- Automate processes using Visual Basic for Applications (VBA) coding
Training Course Content
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.
Course delivery details
This course is offered through The National University of Singapore, a partner institute of EdX.
3-5 hours per week
Expenses
- Verified Track -$99
- Audit Track - Free