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%
來自COMPUTATIONAL THINKING FOR PROBLEM SOLVING的熱門評論
The last week of the course was challenging, but I learned a lot! It was a great introductory course. I would use this to gauge your interest in this field. Worthwhile and you can't beat the cost!
The course is generally good. However, the assignment content and the lecture are not really getting along, especially the Python part. I suggest more "bridging" materials.
Prior basic python knowledge will help with this course. Instructors were great. However the last week and its assignments need to tie in better with the overall course.
An excellent bridge into introductory computer science topics. Professors Susan Davidson and Chris Murphy exposed learners to computer science concepts within everyday problems.
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?