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).

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!

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.

TL, dr: Flawed course in comparison to the first two ones.

The course introduce new concepts, more or less technical to understand what's going on when you try to access web data from an external application, such as a programming language. If you're new to programming like myself, you could feel a bit overwhelmed at times, but with a little patience and dedication, you end up understanding the whole process and why it could be useful to use code to access web data. The instructor is helpful and does a good job in this part.

However, I have two great objections to the course:
The first one is that there is no explanations about libraries and modules. The course relies heavily in them not only for the assignments but for the lectures. If the specialization claims to be for any person without programming language but don't include any explanation about these features, is missing a crucial part for the students to know what they're doing. And sorry but just hearing the instructor says 'type this and it will work' is not a valid explanation, at least for me.

The second one is about the course structure. Because it explains so many new concepts, some of them are treated only at surface level, without providing a deep explanation. I wouldn't have minded do two or three more weeks or even an additional course if this would have given a better understanding of concepts such XML, sockets, REST architecture or JSON. In addition to this, at times some code are explained after need it to do previous assignments so at not few times, I ended up looking for solution on the internet or copy/paste the code provided in the assignment because I couldn't understand what I was doing.

On a side note, although I enjoyed week 6 the most, the videos about APIs usage must be reviewed. Google geocoding requires an API key now so when you type the code and try to access data, it returns an error. The one about Twitter API is directly useless in which you need a Twitter account (I don't have one and don't have plans to have it in the future) to follow the lecture.

It is hard for me to give this anything lower than 5 stars since I'm truly learning much more than I otherwise would have from this course. I can only speak as a learner and not as an educational institution or teacher. With that said, I do understand some of the reviews where it kind of drops you off a cliff and hope that you can work with what they gave you to land safely.

What really worked for me is slowing down and understanding what the code is telling me piece by piece. For the last part, the urllib.parse.encode(parms) function is really just adding a string of key: value pairs to the end of the url, and while that might not mean anything to some reading this, it was a "aha" moment for me. Learning that a lot of this was finding a bunch of ways to display and manipulate key:value pairs really helped me understand some of what seemed to be "jargon".

After knowing that, I realized that other folks have made it REALLY easy with internal programs like "json" and "urllib" to do a lot of the clean-up work for us so we can read and crawl through these webpages just like we would the lists/dictionaries that we make on our own.

I also wrote everything in VSCode in a Jupyter Notebook with language support, so it allowed me to hover over each part of code and it could tell me a short description of what was going on at each part. The Notebook format allowed me to print pieces of code at a time without having to run an entire file. This definitely helped when requesting urls over and over again through Google geocode.

I would say from the very start of the specialization, it is really, really helpful to slow down and understand what is going on and not just be satisfied with an accepted output. I did not have much Python experience at all before this course and it definitely helps to look at a few introductory courses before/after this one. That said, after most assignments I've experimented and tried writing my own code to see if I get the same results. Sometimes my code was a little better/shorter. In fact my only problem really was Chuck's use of variable names. Almost none of my variables look like his at all. There was actually an "input" variable he uses in one of the code3 zip files and interferes with the "input()" function and it's atrocious.

Besides that light-hearted nitpick, I feel that I definitely learned a lot here. I feel confident moving forward with python and web development after doing the assignments. It makes sense.

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.

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.

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

:-)

Whilst covering an interesting and important set of topics within python, I feel this course kind of rushed over it a little bit. While the libraries were introduced, lectures and other materials left me confused as tho all the built in functions, use cases, etc, and often had me do additional research before fully understanding the topic. Lectures also felt a bit more like showing specific use cases, and I was sometimes confused as to why and with what logic specific things were done, for example why specific syntaxes for the data structures that url and JSON functions gave us were appropriate, though this might also be just general unfamiliarity with python given the short time I have worked with it. Besides that, I Liked the topics introduced, the work we did with it and the order in which things were introduced

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

Officially finished this course! 60% done with the specification. My personal takeaway is that every person has their own pace, so I did much research on topics that were new to me outside the classroom (for example: differences between JAVA & JavaScript, comparing list() dict() dir(), etc.).

I would suggest other students to watch supplemental/"bonus chapter" videos, as they somehow explained basic ideas that were not covered in compulsory videos.

Acknowledgement: Web Data accessing is much more challenging than what I learned in the previous 'Zero to one' courses.

The assignments and materials themselves are amazing! They pushed me to learn Python and use libraries actively. Sometimes, I might not be able to get something correct every time, and I believe that's why we have tons of individual notes. At the end of the day, we use our brain and those already-built notebooks to code/solve probs in real life.

"Using Python to Access Web Data" by the University of Michigan is a must-take course for anyone interested in harnessing the power of Python for web data manipulation. The course provides a well-rounded education in web scraping, web services, and data extraction, making it relevant for various fields, including data science, web development, and research. Dr. Charles Severance's expertise, combined with the comprehensive curriculum and practical assignments, makes this course a standout choice. I wholeheartedly recommend it to anyone looking to enhance their Python skills and explore the world of web data.

In conclusion, I am extremely satisfied with the knowledge and skills I gained from this course. It has undoubtedly contributed to my personal and professional growth. Kudos to the University of Michigan and Coursera for offering such a valuable learning opportunity!

I've completed the two previous courses and I learned basic programming, I had few things which weren't ideal. This "course" or section I should say, is a disaster.
Previous issues were the little content available for each course, by the end of it you feel rather void because you expected better quality and more content than 15 minutes max video per week. The only positive were the exercises which you would see in the book at the end of the chapters.
Each course is mediocre as the teaching uses little formal language, which would have been appreciated, it is not like a college "course": the standards are very low, and fails to explain anyway because the explanation is not well prepared and brushes off content. In this last Section: it is not a course, it became worse; became faster, didn't explain content neither in the slides nor the book and the main concepts are barely introduced. It looked like he bored himself while explaining and writing, and it is not an excessive description.
There are at the end of each week course interviews with the creators of the programming languages and of himself traveling the world and having fun which left me perplexed, for obvious reasons for the latter, and for former as the interviews is about concepts and issues not related to the course at all, discussion which the supposed new programmer would never understand and of course I've never learned anything from the interviews, never understood what they were even talking about.
I planned to do other courses like django and web development from the same teacher but the obvious lack of effort in the teaching made me reconsider my learning journey.

"Using Python to Access Web Data" is a fantastic course that introduces learners to the powerful world of web scraping and APIs. Dr. Charles Severance continues his excellent teaching style, guiding students through the process of gathering, parsing, and using data from the web. This course is ideal for those who already have a basic understanding of Python and want to explore how to interact with web-based data.
What I liked:
Clear explanations of web scraping and APIs: Dr. Chuck does an excellent job of simplifying web scraping and using APIs, making it accessible even to those with no prior experience in these areas.
Hands-on projects: The assignments are practical and allow learners to experiment with real web data, which is both engaging and highly educational.
BeautifulSoup and JSON: The course introduces important Python libraries like BeautifulSoup for web scraping and json for working with APIs. These tools are vital for anyone looking to work with web data.
Practical examples: The course covers real-world examples of retrieving data from websites and APIs, helping learners understand how these techniques are used in practice.
Overall:
This course is an excellent step for those looking to broaden their Python skills into web development, scraping, and data retrieval. The hands-on approach, coupled with clear instruction, makes it a valuable learning experience for anyone interested in working with online data sources.