此课程适用人群: This course is for anyone who has taken the first three courses in the Java Programming and Software Engineering Fundamentals Specialization, “Programming Foundations with JavaScript, HTML and CSS,” “Java Programming: Solving Problems with Software,” and “Java Programming: Arrays, Lists, and Structured Data.” To succeed in this course, before starting you should have a good understanding of the following: variables, conditionals, loops, methods, Strings, arrays, lists, maps, Java classes, and the edu.duke custom libraries.


制作方:   Duke University

  • Robert Duvall

    教学方:    Robert Duvall, Lecturer

    Computer Science

  • Owen Astrachan

    教学方:    Owen Astrachan, Professor of the Practice

    Computer Science

  • Andrew D. Hilton

    教学方:    Andrew D. Hilton, Assistant Professor of the Practice

    Electrical and Computer Engineering

  • Susan H. Rodger

    教学方:    Susan H. Rodger, Professor of the Practice

    Computer Science
基本信息
级别Beginner
承诺学习时间4 weeks of study, 4-8 hours/week
语言
English
如何通过通过所有计分作业以完成课程。
用户评分
4.6 stars
Average User Rating 4.6查看学生的留言
Course 4 of Specialization
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制作方
Duke University
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
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评分和审阅
已评分 4.6,总共 5 个 308 评分

tres bon cours

great stuff

good and Engaging course require good understanding of course material to solve the assignment.

Pacing of this course was all over.

Interface and Abstract classes were introduced and the material and lessons were easy to follow. Sorting using bubble sort, caparable, and comparator operators were also easy to follow. The final week presented topics on exception and try/catch/finally, but provided no practical programs for a student to write to ensure the topics were understood.

The problem was in week 3. N-Grams meant to teach some very important concepts about Markov and predictive text, but failed somewhat since the quizes were not clear and the grading a bit harsh. In the quizes, problems were presented and you either had the right output or you did not. There was no checks available that allowed a student to figure out why code produced the wrong output. In other modules (and courses in this series), input was provided and expected out based on the input was provided to verify code was working correctly. Not in section 3 - you wrote the code, took the quiz, and if you got the answer wrong were left scratching your head as to why, since there were really no means to check.

Don't mistake this feedback as saying the course was bad - it was actually quite good. If the course material for week 3 is updated to include clearer instructions and some better checks to ensure code is working correctly then I will change my review from a four star (it's more 3.5 than 4) to a five star.