Using Python to Access Web Data

I have one big criticism of this class. The Python keyword "import" is never explained. The concept of "module" is never explained.

We're just told to cant this magic incantation "import re" and suddenly statements that generated traceback errors suddenly don't. Even more intriguingly, python now seems to recognize regular expressions!

Later, we're just told to cant another magic incantation "import xml.etree.ElementTree as ET" and now there are actually new data types!

How this happens is never explained.

To make this class perfect, you just need to add one -- just one -- lecture which explains what modules are and what importing them does. Take if from "just type this magic incantation," to "this is how we can add functions and data types and methods and expand python."

Python itself is a wonderfully-compact little language, just 33 keywords and just eight data types. Python itself can't interpret regular expressions, can't parse XML or JSON, can't convolve matrices of complex number. What makes Python such an amazing language is that one of the keywords is "import." With import, we can expand python to interpret regular expressions, parse XML or JSON, and convolve matrices of complex number too. You can even write a program that can convolve matrices of complex numbers that come from a web-based source in the JSON, all in one program. This is why it's so important to understand modules and libraries of modules and understand what import does. It shouldn't be taught as just some mysterious magical incantation.

Students should be taught that there are standard libraries of python modules available, that there are countless non-standard libraries and modules which are also available to "use at your own risk," that many companies and institutions have in-house libraries, and that they can even learn to create their own libraries if they want to (though the mechanics of this can be left to another class).

As I mentioned in the previous reviews about this Specialization, all these courses are meant for beginners without previous programming experience and difficulty of courses rises gradually.

Thus, the first course was a real piece of cake, second got a little tougher and this one is the first course that really took me some time to finish it. This time I really had to listen to some lectures twice, to debug my code a hell lot of times and to stick to the sample code a lot.

Students, who have programming experience might still think that this course is too slow and easy, but it is a great way for the beginner to learn python.

However, it seemed like Dr.Chuck had too much stuff to show us in a single course, that made it impossible for him to explain everything that was done, which was done in the 2 first courses.

Now it's just "type this, you won't know what it is and why you type it, but it'll make your program work". So you end up copy pasting Dr.Chuck's code without knowing what you're doing.

I would have preferred this course divided into more courses to go deeper in the modules or functions, so we can understand pretty much everything we do, and write the code from scratch. It could even have been a 10 weeks course instead of 6 and I wouldn't have minded.

All in all, I'm satisfied with what I've learned, but I had to go to many other websites to understand the course material.

I really enjoyed the first two courses of Dr. Chuck's Python for Everybody Specialization -- but not this one. As some other reviewers have already stated I, too, felt increasingly frustrated and somehow left alone during this course. Most of this course's assignments were way too difficult and I had to search the web for hours to find some help to solve them. Or, quite honestly, I had to cheat my way through them, because I just didn't know what to do anymore. There are of course the discussion forums where one can state one's problem - but although the staff and mentors are really quick with replying (thumbs up for that), their tips are often way too general and not helpful at all.
After taking this third course I will definitely not continue with the Specialization, as I originally planned to, simply because in comparison to the first two courses, this third course is way too difficult and frustrating!
Also, in my opinion, Dr Chuck tries to squeeze in far too many different topics and different programming langauges into this course, instead of really just focusing on Python itself.
I completed this course, yes, but it left me with a very frustrated and unsatisfied feeling. I don't think I was really able to learn a lot from it, which is really a pity, since I enjoyed the first two courses so much.
Sorry for the bad feedback, but this is honestly how I felt about the course!

I am working my way through the Python Specialization. The first two courses were fantastic. This course, "Using Python to Access Web Data", was a bit of a struggle. While I still like Dr. Chuck's on camera teaching and the examples he provided, the course assignments and quizzes in this tranche require knowledge that is not provided in either the book, video, or slides. In a few instances, knowledge needed to complete an assignment was provided in a later learning session. On more than one occasion I found myself saying...I wish this had been presented in the previous week.

In one or two of the assignments, the code that was provided as the primer included commands not taught until later in the course. This left me trying to figure out the relevance to the current assignment (there was no relevance). Ultimately, the geocoding references had to be deleted (or ignored) from the starting code to make the XML retrieve work.

The 'decode()' command provide to be very useful to the XML assignment. I don't think enough explanation and emphasis was placed upon this when taught. Once you apply this to your code, the XML output when printing becomes so much more useful if you are attempting to understand the XML structure and hierarchy.

The ElementTree library is not well explained. In fact, all libraries presented in this course to date are not well explained. They get blackbox treatment in the code examples and assignments. The Python website has a lot more information for those seeking a better understanding (https://docs.python.org/3/library/xml.etree.elementtree.html).

There is a data return in the XML assignment which I think is a list of memory locations. This is not explained anywhere in the course (in fact, I am guessing that the returned bits are memory locations...I still don't know for certain).

There are a few computer history video's in the course that are over my head. I'm still not sure what REST is and how it governs HTTP transfers. That said, it probably would be an interesting topic if I knew a little more. Maybe if I had taken Dr Chucks other class on networking it would have had more value to me?

All this said, I like the fundamental information in this course and I like what I am learning in Python. This review is not to discourage. Rather, you should take the class and realize there are a few shortcomings. Don't be surprised if you struggle through a few assignments.

Although my specialty is zoology, I signed up and paid for this course (one in a series offered by them) to learn a little about Python which intrigued me for some reason.

The course gives a somewhat disjointed, quick overview of using Python to access web data, but Professor Severance does try to touch shallowly on a good array of the relevant subject matter.

The real sin, however, (and the entire reason I’m taking the time to post this review) is to be found in the course’s abomination of a forum, where the “teaching assistants” are aggressively unhelpful. A teaching forum is intended to be a resource for students who have hit a wall in an assignment and need a few well-placed words of guidance to get them over a hump, but there is none of that found here.

Right around week 5 of this 6 week course was an assignment that a fair number of students had trouble with (judging by the number of questions in the forum) . I read several student to teaching assistant exchanges on the forum where a student just couldn’t figure out that bit of code with the vague “guidance” they had received, and when they had the temerity to persist with their questions, were cut off at the knees by the teaching assistant, and instructed to stop asking . . Really condescending, uncalled for, and shocking, quite frankly, in an educational setting.

I would highly recommend that if you want to learn to use Python to access web data, or any of the other courses in the Python for Everybody series at the University of Michigan, you seek out some other, more professionally run courses where you can get actual assistance if you have a question. There are certainly plenty to choose from.

I just completed the course. It is excellent, but needs a few bug fixes.

The Week 5 Chapter assignment references the wrong exemplar (not wrong, per se, but far more complex than a simpler example covered in the lectures that transfers better to the assignment).

This threw a lot of people and protracted completion of the exercise. A plurality of people who noticed this whined. Apparently, the course shell has not been updated in 2 years.

The code snippets reference the P4E website, which is Dr. Chuck's open source version of the course. The links to the snippets should be given in the course shell, rather than requiring the student to navigate over to the P4E website, dive into the Resources area, then scan to find the snippet.

As one reviewer noticed, there are 2 questions in the Week 6 chapter quiz on REST, but no mention of REST in the lectures, and only a cursory mention of it in Chapter 13 of the text.

I also think that the GeoCoding example covered in the lecture videos needs to be broken down into steps. Perhaps it could be developed incrementally--showing the outputs generated and data structures used at each step. I ended up doing this myself, but I have significant prior knowledge.

There is also little use of functions in the course to-date. It might be good to enforce that as a precept of modular design and to inculcate good habits.

I used https://repl.it throughout the course, despite the recommendation that students invoke Python from the shell and use the platform agnostic Atom editor. Repl is a great learning tool and has a social component these days that has some of the collaboration functionality of forums like Slack. I think the course would run better this way.

Overall, this is one of the better classes on Python out there. I took an introductory Data Science oriented version of a Python course at Harvard and wish Dr. Chuck had been the instructor.

On to Course 4: Using Databases with Python...

jerald_cole @ alumni DOT harvard DOT edu

:-)

This is the third course of a five-part "Python for Everybody" specialization. The first two courses I found quite easy although I have some previous coding experience (FORTRAN, C/C++). This course was more challenging. Week 1 is about installing Python, so it's the same material from the first/second course. In Week 2 the instructor (Charles Severance) talks about regular expressions. This was quite well explained I thought. There was a question in the graded quiz that confused me though. I went to the discussion forum to find that someone else was also confused by this question, but the mentors wouldn't help because it was a graded question! So I still don't understand the answer.

Weeks 3-6 are about extracting data from web pages, be they plain text, html, xml or json. He uses libraries in Python to handle this data, including a third-party library called Beautiful Soup for the html data. I think he should've delved deeper into these libraries because I was left without a basic understanding of how they worked, and I was just copy-pasting the code that he uses when utilising these libraries. In Week 6 the section on APIs was rushed I felt. For example he mentioned secret keys but didn't explain how they worked and why we were storing them in a separate file. Also the first code he shows to access the Google Maps API no longer works (an updated version is shown later in the course however).

As in the previous two courses, I liked the bonus interviews he did with other leading figures in the programming and internet world, particularly the interview with Leonard Kleinrock on the beginnings of ARPANET. However the bonus hours videos of him meeting other Coursera students don't add much to the course imho. He also has a video of him singing on stage! Whilst it is fun I don't think it should be part of an academic course.

This course has the most practical use out of the three in this series so far, but some topics were not explained deeply enough, particularly the section on APIs. As for the first two courses, I don't recommend this as a one-off £35 Coursera course, but as part of a £42 monthly subscription I think it's good value.

With this review, you must understand, a major part of this review is because of my interest/expectations/etc., what I was looking for from the course. If you are interested in “fully engaging” in Python, becoming a computer scientist, etc., this course if fine. Me, I’m an engineer by profession. About every 5 years, I go back and take a class to keep my programming skills up. So, my interests in programming would be about 80% math implementation, 20% string/list/character manipulation. This course was all string/list/character manipulation, I felt. So, I was turned off by the course.

This course definitely isn’t a beginner Python course. You need to have had Python experience before taking this course.

Other things I will describe briefly. They are only examples.

First, I didn’t know we would get into things like XML and JSON has deeply as we did. If I wanted to learn XML or JSON, I would have taken a course on those. I was interested in learning Python, not XML and JSON.

Given that, I couldn’t understand why we were learning things in this course. I could understand much of what the programs were doing. But, “why” learn this information? Like, in one program, I felt I have done the manipulation much, much easier and faster with “copy-n-paste” and MS Excel. So, why make a Python program to do the manipulation? I couldn’t tell why.

Given that, I felt that Dr. Chuck was doing more along the lines of “forcing” this information onto us during this course. Something like, not a quote but what it seemed like, “Python can do this, so just do it. Don’t worry about learning it. Just do it.” But, then, he wants us to demonstrate our ability in the knowledge and programming at the end of the chapter?

In summary, again, if you want to get “fully engaged” in everything Python can do, aka become a computer scientist, this course will probably be good for you. But, for me, sorry, but it lacked what I look for from a programming course.

I have one big criticism of this class. The Python keyword "import" is never explained. The concept of "module" is never explained.

We're just told to cant this magic incantation "import re" and suddenly statements that generated traceback errors suddenly don't. Even more intriguingly, python now seems to recognize regular expressions!

Later, we're just told to cant another magic incantation "import xml.etree.ElementTree as ET" and now there are actually new data types!

How this happens is never explained.

To make this class perfect, you just need to add one -- just one -- lecture which explains what modules are and what importing them does. Take if from "just type this magic incantation," to "this is how we can add functions and data types and methods and expand python."

Python itself is a wonderfully-compact little language, just 33 keywords and just eight data types. Python itself can't interpret regular expressions, can't parse XML or JSON, can't convolve matrices of complex number. What makes Python such an amazing language is that one of the keywords is "import." With import, we can expand python to interpret regular expressions, parse XML or JSON, and convolve matrices of complex number too. You can even write a program that can convolve matrices of complex numbers that come from a web-based source in the JSON, all in one program. This is why it's so important to understand modules and libraries of modules and understand what import does. It shouldn't be taught as just some mysterious magical incantation.

Students should be taught that there are standard libraries of python modules available, that there are countless non-standard libraries and modules which are also available to "use at your own risk," that many companies and institutions have in-house libraries, and that they can even learn to create their own libraries if they want to (though the mechanics of this can be left to another class).

First course in the specialization that really gets you going (as promised in the two previous classes). It also will take some more effort, but you can use the knowledge built in the two previous courses. It is rightfully classified as "Intermediate" I think , it can be a bit challenging. I do agree with other reviews that sometimes you get the feeling that dr. Chuck struggled to put a lot of information in the course without getting into too much detail but overall I think he managed to do it quite well, since personally I think you need to know at least something about e.g. XML and JSON and if you're really interested you can always dive further, but it is hard to draw a line where to stop. I think he touched the content enough beyond the surface, without diving too deep, but it depends a bit on the background of the student and sometimes it gives an impression of a hurry in-between (which makes your response "wait, what...?". Where in the first two courses really everything was explained fully. What I don't agree about with other reviews, is that the assignments are too hard to make and leave you without support. Personally I think the support is great and fast, but the idea is not that people should give you the exact locations of your error and a solution. And yes, it can be very tempting to just copy code without knowing what it does, but that's not why you enroll in a course, right? There are a few imported libraries that you just import and for which you copy and paste the code to call it, but personally I don't think for the rest you get incomprehensible content to process. I had the experience twice that I thought I didn't completely follow what to do and then I just went back to the lecture and materials to try to grasp it better.
Overall: I think it is a good and recommendable course again, but you need to take your time to learn if you are less experienced, maybe first play around some more with the basic concepts and pull out other resources on the web to try to grasp it better.

I rate this course as an initial foray into data scraping off the web. It certainly provides insight into different methodolgies for doing this and to parse data into useable information. I say initial foray into the subject, for clearly there is a huge well of information out there which a course of this length and complexity cannot fully adress.

Unfortunately, the course created more questions than answers in knowing where to go and look for data (which URL's). While Google provides a wealth of links, I would want to drill down deeper into information specifics, rather than just visiting the different web sites.

Clearly this course is very introductory, but it did whet the appetite to study web data accessing in more detail. I am looking forward to futher exploring the opportunities out there.

This third course applies and builds on the basic knowledge from the first two python courses. Especially interesting is the information on regular expressions, which kicks this course off. Following this the course gears up into a higher transmission focusing on using python with web browsers and reading webpages. Beautiful Soup gets covered as well as how to deal with XML data. So far so good.
Unfortunately the course loses itself suddenly in Java Script Object Notation and dealing with Twitter and Google Maps to the point where the amount of knowledge required does not match the content and quality of the classes.
Also ' dr. Chuck' seems more and more concerned with his self-promotion in the bonus video material that is provided each week, rather than focusing only on content. The age of the material (the course was ' shot' in 2015) also starts to show with the assignments that often lack sufficient information for students with English as a second language or jump into a level of complexity that is possible more than the basic student can understand.

As I mentioned in the previous reviews about this Specialisation, all these courses are meant for beginners without previous programming experience and difficulty of courses rises gradually.
Thus, the first course was a real piece of cake, second got a little tougher and this one is the first course that really took me some time to finish it. This time I really had to listen to some lectures twice, to debug my code a hell lot of times and to stick to the sample code a lot.
Students, who have programming experience might still think that this course is too slow and easy, but it is a great way for the beginner to learn python.
The only problem that seems to appear is new coursera policy, that doesn't allow you to submit assignments before you pay for the course, e.g. you can only get access to theory unless you pay. But there is a solution - Dr Chuck has created his own website to complete these courses https://www.py4e.com//
To sum up: great course, uprising difficulties, recommend to enroll after finishing previous courses. 10/10