[UPenn] Computational Thinking for Problem Solving

Learning Computer Science and Coding after many years of working in the Social Science and Language field makes me feel that I need to think differently when studying coding. Thus, I chose to take this course, which was very intriguing from the beginning since I can apply this way of thinking not only when I work on Coding but also in so many ways, from relatively small decisions in daily life to problem-solving situations in other fields. I am very much excited to take this course to expand my way of thinking and enhance my design of Algorithms.

Source: Penn Engineering

 

Decomposition
• Breaking a complex problem into more manageable sub-problems.
• Putting the solutions to the subproblems together gives a solution to the original, complex problem.

Pattern Recognition
Finding similarities or shared characteristics within or between problems.
• Makes the problem easier to solve since the same solution can be used for each occurrence of the pattern.

Data Representation & Abstraction
Determining what characteristics of the problem are important and filtering out those that are not.
• Use these to create a representation of what we are
trying to solve.

Algorithms
Step-by-step instructions on how to solve a problem.
• Identifies what is to be done (the instructions) and the order in which they should be done.

 

I learned from this lecture that a computational way of thinking is not only for a coding or IT-related field of studies or work but for any situation, studies, or work in our life. That is cool, isn't it?

 

You can also start this course on Coursera right now!

https://www.coursera.org/learn/computational-thinking-problem-solving

Computational Thinking for Problem Solving