Computational Reasoning with Microsoft Excel from 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.

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

What's inside

Learning objectives

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.

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.

Syllabus

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches computational problem-solving, a valuable skill in many industries

Taught by Jonathan Sim, an experienced instructor

Examines data analysis and modelling techniques, which are highly relevant in business and research

Develops critical thinking and problem-solving skills, essential for personal and professional growth

Requires familiarity with Microsoft Excel, which may be a barrier for some learners

Focuses on the fundamentals of data analysis and modelling, which may not be in-depth enough for advanced practitioners

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Computational Reasoning with Microsoft Excel with these activities:

Review course materials

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It is important to refresh your understanding before beginning this course since every session builds on previous materials.

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Read the syllabus
Review the course schedule
Preview the course materials

Learn how to use a data analysis tool

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Learning how to use a data analysis tool is a great way to improve your data analysis skills and make your work more efficient.

Browse courses on Data Analysis

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Choose a data analysis tool
Find a tutorial
Follow the tutorial

Read The Visual Display of Quantitative Information

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Data visualization is an essential skill for data scientists. This book will help you learn the fundamentals of data visualization and how to create effective visuals that communicate your findings clearly and concisely.

View The Visual Display of Quantitative Information,... on Amazon

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Read the book
Take notes on the key concepts
Create a data visualization project using the techniques you learned

Five other activities

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Solve data analysis problems

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Solving data analysis problems is a great way to practice your data analysis skills and learn how to apply them to real-world problems.

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Find a dataset
Identify the problem you want to solve
Analyze the data
Find a solution

Create a data visualization dashboard

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Creating a data visualization dashboard is a great way to practice your data visualization skills and learn how to communicate your findings to a wider audience.

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Choose a dataset
Clean and prepare the data
Choose the right visualization types
Create the dashboard

Create a computational problem-solving notebook

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Creating a computational problem-solving notebook will allow you to catalog the problems in this course and to practice solving them.

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Choose a programming language
Set up a notebook
Start solving problems

Attend a data science workshop

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Attending a data science workshop is a great way to learn new skills and network with other data scientists.

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Find a data science workshop
Register for the workshop
Attend the workshop

Participate in a data science competition

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Participating in a data science competition is a great way to test your skills and learn from others.

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Find a data science competition
Register for the competition
Build a model
Submit your model

Career center

Learners who complete Computational Reasoning with Microsoft Excel will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts look at large sets of data to find trends. They analyze this data to answer business questions, identify problems, and make recommendations. This course covers the process of computational problem-solving, which can help Data Analysts to improve their skills in analyzing data and solving business problems. Additionally, the course covers Microsoft Excel, a tool that is often used by Data Analysts to manage and analyze data.

See salaries and explore the career path for Data Analyst

Financial Analyst

Financial Analysts use data to make recommendations about investments and financial decisions. This course covers data analysis techniques that can help Financial Analysts make better use of data to make more informed decisions. Additionally, Microsoft Excel is a tool that is often used by Financial Analysts to manage and analyze data.

See salaries and explore the career path for Financial Analyst

Business Analyst

Business Analysts study the needs of an organization and design solutions to help the organization achieve its goals. This course covers the process of computational problem-solving, which can help Business Analysts understand the needs of an organization and then come up with solutions to meet those needs. Additionally, Microsoft Excel is a tool that is often used by Business Analysts to track progress and measure results.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems that arise in business and industry. This course covers mathematical and analytical techniques that are used by Operations Research Analysts to solve problems. Additionally, Microsoft Excel is a tool that is often used by Operations Research Analysts to manage and analyze data.

See salaries and explore the career path for Operations Research Analyst

Market Researcher

Market Researchers collect and analyze data to understand customer needs and preferences. This course covers data analysis techniques that can help Market Researchers better understand and interpret data. Additionally, Microsoft Excel is a tool that is often used by Market Researchers to manage and analyze data.

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Software Engineer

Software Engineers design, develop, test, and maintain software systems. This course covers the process of computational problem-solving, which can help Software Engineers better understand the needs of users when designing and developing software systems. Additionally, Microsoft Excel is a tool that is often used by Software Engineers to manage and analyze data.

See salaries and explore the career path for Software Engineer

Statistician

Statisticians collect, analyze, interpret, and present data. This course covers data analysis techniques that can help Statisticians better understand and interpret data. Additionally, Microsoft Excel is a tool that is often used by Statisticians to manage and analyze data.

See salaries and explore the career path for Statistician

Data Scientist

Data Scientists use data to build models and make predictions. This course covers data analysis techniques that can help Data Scientists build better models and make more accurate predictions. Additionally, Microsoft Excel is a tool that is often used by Data Scientists to manage and analyze data.

See salaries and explore the career path for Data Scientist

Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze financial markets. This course covers mathematical and statistical techniques that are used by Quantitative Analysts to analyze financial markets. Additionally, Microsoft Excel is a tool that is often used by Quantitative Analysts to manage and analyze data.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. This course covers mathematical and statistical techniques that are used by Actuaries to assess risk and uncertainty. Additionally, Microsoft Excel is a tool that is often used by Actuaries to manage and analyze data.

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Computer Scientist

Computer Scientists design, develop, and maintain computer systems. This course covers the process of computational problem-solving, which can help Computer Scientists better understand the needs of users when designing and developing computer systems. Additionally, Microsoft Excel is a tool that is often used by Computer Scientists to manage and analyze data.

See salaries and explore the career path for Computer Scientist

Risk Manager

Risk Managers identify, assess, and mitigate risks. This course covers risk management techniques that can help Risk Managers better identify, assess, and mitigate risks. Additionally, Microsoft Excel is a tool that is often used by Risk Managers to manage and analyze data.

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Portfolio Manager

Portfolio Managers manage and invest funds for clients. This course covers data analysis techniques that can help Portfolio Managers make better use of data to make more informed decisions.

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Investment Analyst

Investment Analysts research and make recommendations on investments. This course covers data analysis techniques that can help Investment Analysts make better use of data to make more informed decisions.

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Financial Planner

Financial Planners help clients plan for their financial future. This course covers data analysis techniques that can help Financial Planners make better use of data to make more informed decisions.

See salaries and explore the career path for Financial Planner