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Statistical Thermodynamics: Molecules to Machines(으)로 돌아가기

카네기 멜론 대학교의 Statistical Thermodynamics: Molecules to Machines 학습자 리뷰 및 피드백

3.8
별점
44개의 평가
10개의 리뷰

강좌 소개

Modern engineering research focuses on designing new materials and processes at the molecular level. Statistical thermodynamics provides the formalism for understanding how molecular interactions lead to the observed collective behavior at the macroscale. This course will develop a molecular-level understanding of key thermodynamic quantities like heat, work, free energy and entropy. These concepts will be applied in understanding several important engineering and biological applications....

최상위 리뷰

필터링 기준:

Statistical Thermodynamics: Molecules to Machines의 10개 리뷰 중 1~10

교육 기관: Jacques D

2017년 5월 14일

The content may be correct and up to date, but the lecture is just a reading of pdf files that are largely incomprehensible unless one has already taken a course in statistical thermodynamics. Every other equation introduces new terms with no basis for understanding them. This is apparently also unsupported as the discussion is not active. The "quizzes were ludicrous involving trivial questions and plug and chug questions that required lots of unit changes and no understanding whatsoever. The last quiz was not on the last module, but the whole class and was twice as long. It included a question on adsorption which was in the next module. All in all, this material will be useful for reference after I take a real stat. thermo. course. Coursera should not have this course in the catalog.

교육 기관: Kevin K

2017년 7월 29일

Course is very advanced. Listed as "Intermediate," but that should be interpreted as "intermediate for a graduate student in physical chemistry." Math is high level. Lectures are well-produced, but explanation is minimal, and a large number of advanced topics are covered in a very short time. Homework is poorly designed and not very relevant to the lectures, but not too hard if you stick with it. Forums not active or useful. Not a good course if you need close instruction to master many of these topics. Nevertheless, I found the course to be very useful as a survey of chemical/physical applications of thermodynamics. Great way to get a broad overview of the terrain for more in-depth future study.

교육 기관: Hristo G

2017년 1월 22일

Without a comprehensive background in thermodynamics (which I do not have), advanced mathematics and statistics, this course is extremely hard to impossible to follow. Formulas come out of nowhere and the explanation of the conceptual theory is very thin.

교육 기관: Sayan s

2018년 7월 1일

This course is advanced level stuff.You got to have high understanding of probability distributions and also a lot of integral calculus is required.

교육 기관: Ganapathy K

2017년 7월 10일

The lectures and the handouts are not very clear. The lecture does not have any explanatory information.

교육 기관: Hsiang-Ju K

2017년 4월 24일

Not bad, but would be better if the course could explain more on the details.

교육 기관: Sreedath P

2016년 11월 11일

Great experience

교육 기관: Jonathan G H

2020년 5월 26일

Excellent Handouts and Brief Videos. Great Evaluation methods, recommended for those who know Calculus and Statistics.

교육 기관: Richard A P R

2020년 6월 18일

Some times is complicated

교육 기관: Ricardo A V

2021년 10월 26일

the course is pitched at graduate level with no feedback on what and why went wrong.... I am giving one star, because 80% score, is a requirement to pass exams....There is no feedback and no info on your rights or wrongs, a consolidated score is shown, only... Pushing you to answer each individual question at the time and not the whole quiz at once.... The pass grade should be lowered to 60%....Worst of all, this course IS NOT SELF CONTAINED. Actually, you must resort to subject material involving third parties . No CMU nor Coursera.org sanctioned material is enough to pass this course