Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.
Computational Thinking for Problem Solving宾夕法尼亚大学
- 5 stars80.55%
- 4 stars12.71%
- 3 stars3.28%
- 2 stars1.23%
- 1 star2.21%
来自COMPUTATIONAL THINKING FOR PROBLEM SOLVING的热门评论
An excellent bridge into introductory computer science topics. Professors Susan Davidson and Chris Murphy exposed learners to computer science concepts within everyday problems.
IT is a very good course. That being said, week 4 should be spread over two weeks, and have more explanation in order to make the projects more manageable. I struggled with the last two projects.
Great course - the non-programming parts (making flow charts etc) were actually more difficult than the programming (simple Python programming - my first time programming in python)
Course content is good, graded assignments are good, I just had problems with my assignments in week 4 as I easily became confused with the implementation of all the lessons combined.
Do I need to know how to program or have studied computer science in order to take this course?
How much math do I need to know to take this course?
Does this course prepare me for the Master of Computer and Information Technology (MCIT) degree program at the University of Pennsylvania?
Where can I find more information about the Master of Computer and Information Technology (MCIT) degree program at the University of Pennsylvania?