Ratings and Reviews for Introduction to Data Science in Python

作业描述不清楚，有歧义！！！

It does not matter if you have intermediate python level of experience. You should not go through the material so fast and not explain properly what the specific code does. I understand that we should seek outside resources if we don't understand something but thats not an excuse for providing fast answers to what a code does and not provide explanations to specific code. All I saw in this introduction was fast typing lol.

An excellent course, my code is more pandorable now.

Immediately after this class I was able to much more effectively visualize tabular data on my research project and build more effective notebooks to share with my peers.

Assignment 3, question 1: The autograder would mark this answer correct even when the data in the DataFrame was wrong. I discovered this after I answered the question, was told it was correct, but I produced wrong answers for subsequent questions that depended on the first one. Messages from fellow students in the forum helped me track down the problem. Assn. 3, question 2: This was worded very awkwardly and the Venn diagram seemed to contradict the question rather than clarify it. Assn. 4, question 1 ("get_list_of_university_towns"): The function template provided has a long comment block that seemed to be complete instructions for what the function should do. However, there are two other different versions of the instructions for this assignment in the Coursera course resources section and Google Drive. If the function template includes instructions in the comments, they should be complete. Otherwise, don't show them at all and let the student get the instructions from the other document. Also, the course's "Resources" section doesn't seem like the correct place for these instructions. They should be under the "Instructions" tab of the assignment submission page. The instructor, teaching staff, mentors, etc. are almost completely unhelpful or extremely slow to answer questions. With regards to my forum postings for assn. 3, a staff member replied only recently, about two weeks after I asked the question. Since then, I've completed that assignment and the one following it! The course videos are difficult to watch. Whenever Mr. Brooks shows how some code works in Jupyter Notebook, he uses a full-screen view of his browser. On my laptop with a 15-inch screen, his font is a little too small to read easily. I need to concentrate so much more on deciphering the screen that I can't easily keep up with what he is saying. Sometimes I wanted to view the course video on my phone or mobile device. At those times, it was impossible to read the screen being shown. I recommend these alternate ways of showing the code: Use slides. Students usually don't need to see the instructor typing in real-time. Show a slide with the code and the result. Use a large font. If showing real-time input and results is important for a specific question, use a large font or zoom in the display as much as possible. There were some small mistakes made in the videos and assignments that make me think all the materials need some proofreading and updates. Overall, I'm glad I took the course. I wish several things were better, though. I'm looking forward to the next course of the specialization (data visualization), which is the one I was most interested in taking. I took this course because I would need it for the final certificate and I wanted to be sure I didn't miss any information that would be helpful in the second course. I thought maybe the first course wouldn't be interesting to me, since I have many years of Python programming experience. However, I was pleased to find that the course covered a lot of pandas features and some of the mathematics and statistics techniques that I haven't used in many years, so those contributed to making the course challenging. I would prefer to have done without the additional challenges related to autograder technical shortcomings, though.

Now Pandas and I are one.

Course content was really good as it focused more on practical work rather than just theory. The last assignment was difficult.

Course videos provide good examples of using methods, but prepare to teach yourself from StackOverflow when completing the assignments.

Perfect place for beginners to learn data science.

Excellent course, auto-grader + assignments can be frustrating at times but other than that all good. Many thanks. Steve