it becomes easier wand clearer when one gets to complete the assignments as to how to utilize what has been learned. Practical work is a great way to learn, which was a fundamental part of the course.
The syllabus of the course takes you in a roller-coaster ride.\n\nFrom basic level to advance level and you won't feel any trouble nor hesitate a bit.\n\nIt's easy, it's vast, and it's really usefull.
By Shilpa K N•
By Ann-Katrin M•
Worst of the IBM Data Science Prof. Cert. so far. I disliked almost every part of it.
Typos throughout all slides and exercises, labs almost never worked online and had to be downloaded, transcripts are off, responses in the discussion forum were late and/or not always friendly (especially to some seemingly knowledgable participants who pointed out code flaws or such - just followed some of the threads and was irritated by some responses), but amongst all the flaw that makes me think about quitting this certificate this course is part of: absolutely no clear framework obvious. What are the main questions this course answers apart from just giving us a bunch of information? Where are we and which goal will we reach, i.e., what will we be able to do with the knowledge? As someone who has been teaching at big international universities, I would argue that the story of this course is lacking or absolutely unclear and there was not much though given in terms of pedagogy. I passed the final exam right away with 100% even I didn't feel like a learned a lot I could really apply. That being said: I don't want to participate in a course just to pass and get the badge. Instead, I would like to learn something that could help me right away. Unfortunately, for this course, this was in no way the case. I very much hope the next one will be better or I will quit and leave Coursera.
By Ian M S•
I struggled to learn with this course. I have some experience coding with Python already and feel like the Python beginners course from University of Michigan (Python for everyone) was much better at learning Python for data analytics even though the course objective was more to learn about Python rather than data analytics. I didn't like the clunky and cluttered feel of programming in Jutyper. Previous courses I've taken in Python, the video or lecturer would usually code in the shell or an IDE and you'd see the code being done, you'd go practice in an uncluttered IDE where you could debug things easily and I felt like I learned quite easily. This course kind of just lectures through the code and uses visuals to represent the program which I feel is not a good way to teach coding/programming. The beginning weeks were easy because I knew all the content, but I could see it was taught using poor methods in my opinion. When it got to the material at the end which I'd never learned before, I could really feel how slow and difficult it was to retain the information being presented in the videos. I think it would help a lot by doing videos in an IDE and provide a textbook to easily refer back to the content instead of having to click through a video to do so.
By Daniel V•
The worst course I've taken so far. I used to learn on udemy before switching to Coursera because of more well-known providers. This entire IBM Data Analyst Professional Certificate has been mostly way too easy. Explanations don't seem to be technically accurate and simplify concepts a lot. Especially the in the Python module, the basics of programming are skimmed through while the exercises are designed at a significantly more difficult level. A lot of students seem to be frustrated with this part and apparently, nothing is being done to improve this course. Why people are still taking it? To have some certificate from a reknown company on their LinkedIn profile. Do people actually learn in this course? Yes, but only because nothing is being taught here and students are forced to do their own research to solve the exercises.
Basically just an interactive advertisement for IBM's new product. Videos aren't very helpful as they show snippets of code without the context in which they would be applied in an actual program. Labs are okay but they use the aforementioned IBM product, and it honestly isn't that great and it isn't something someone using python to do data science would use in a professional setting. The information given about Pandas and Numpy is embarrassingly lacking so the point where doing the final lab is nearly impossible unless you already know what you're doing or you search for information elsewhere. Not why I pay money for Coursera. Wish I could have my money and time back honestly.
By Lluvia Z•
I'm not sure which parts of the lessons are advertisement and which parts are actual exercises that need to be completed. You are instructed in each segment (so hundreds of times) to not forget to press Shift-Enter for your instructions to be run which is annoying for something so simple. Then the lesson throws you into the deep end by telling you to get an account of gethub using gist to save your jupyter thing and you end up completely lost after clicking on too many links. I might have two accounts of gethub or none--I have no idea.
By Francisco J C G•
I had been taken several courses with Coursera but this data science specialization lacks good planning and clear directions to complete. I asked many times the same question. I was stuck in the last assignment of week 5 and requested help but the responses were not adequate, I contacted the teacher assistants and even the instructor and just received an email to contact Coursera services. They just ignored me; I'm not sure how many students they have but several others have the same issue with Week 5.
By Reinaldo O•
I'm really disappointed with this course. I'm totally new to Python and I can confidently say that I merely grasped around a 20% of the whole content. Some videos are extremely short and fast. If you are new to this programming language, then it will be extremely hard to follow in those cases. And regarding the Hands-On Labs, some of them are good, but a lot of them teaches stuff like you are already familiar with Python, and not a begineer.
By Claudia S•
The third party tool is completely unreliable and it makes this course dissapointing and frustrating.
I wasted too much time trying to make it work, since it was either under maintenance or issuing bad gateway errors.
From the discussion boards, I saw that I was not the only one getting this type of errors, so it would be nice if a better tool could be used or maybe provide alternate instructions to use those Jupiter pages in Watson.
By Alan L•
In my opinion, this course was very poorly constructed. The videos were OK, but the labs contained exercises that were very difficult to understand (because of grammar, syntax, etc.). It is hard enough to try and understand the python language. When the English language is not used appropriately, it can make understanding assignments very difficult. I posted several comments asking for help and never received a single reply.
By Glen v U•
There's no way this should be considered a "Beginners" course. Exercises in labs for week 3 and 4 are very hard. The videos are very understandable but the lab excercises are too difficult. There are way too many gaps in information. The labs seem to introduce everything nice and simply, but then hit you with an exercise that is way to difficult and often uses techniques that have not been explained at all!
By Nicholas P L•
This course is not beginner friendly. It jumped right into the meat of things without proper explanation of terminologies, logic, and reasoning. Other than that, the videos are so hard to follow because the narrator talks so fast and the slides go by so quick. If you have expereince with Python, then this is recommended, but this is far from the "Beginner level" that this course is advertised as.
By Ιωαννης Π•
This course does a really good job to include and teach as much of python programming principles as possible in as little time as possible. I put a 1-star however, only because I expected that there was more step by step and gradual teaching and instructions on applying the theoretical concepts on data management. The progress curve in the labs applications was really steep unfortunately!
By Andrea M•
Lot's of good content. But the labs are very superficial and they just repeat what shown in the videos. The quizzes are too easy and they do not push you to actually apply what you learned. The final assignment was ridiculous. Just using Pandas to import some data, nothing more, no loops, no if statements, no analysis of the data. Continuing being quite dissatisfied with this certificate.
By Yuval S•
This course was not well designed. It needs intensive editing and rewriting.
The author emphasize the use of IBM cloud products, but the course needs to elaborate in this area if this is the desired target.
Not enough explanations were dedicated to the Python language itself. To succeed you must know some Python before you learn the course, or learn during the course from other sources.
By Ahmed A•
Bad videos.. Many methods and functions in the lab are not explained in the videos
To complete this course I spent most of my time reading documentations and searching to understand what is said as there is no enough explanation or even resources to read from.
(Maybe this method suits you but I didn't like it)
Classes in IBM Data Analyst track seem to be for marketing purposes. They force you to sign up for IBM products, provide your personal information and credit card number, and then it doesn't even work. You really don't learn much in the actual classes, they just seem to want to advertise IBM products.
By Cem K•
Absolutely worthless course. Waste of time. You will only get begginner knowledge after listenin to videos with tedius useless information. I knew python before and i watched in horror and disgust how horrible topics were covered and how unnecesarily complicated they were forced to become.
By Ahmet C•
Examples in the videos was not good, at least giving some examples for necessary functions in videos would be good, If you don't want to put new videos than at least give students the documentation link to guide them so they can learn themselves with parallel to labs.
By leonardo c•
IBM should be ashamed of issuing such a patchy-mess up and chaotic material using its brand. Google data analytics course is way better in case you want to actually learn at leas something regarding data analysis / data science.
By YASHVIR I•
Lab is not working. I am not able to access any of the hands-on lab exercises.
By Anthony N G•
This course was a perfect introduction to python for data science. I already have a B.S. in political science which required a few semesters of statistics. We mainly used Excel and SPSS. I wish I had taken a course like this because I’ll say that I much prefer Python to SPSS and Excel. I find Python more functional but far less user friendly. What helped a lot here was that I have a background in windows and pc hardware. I also have a little experience with Linux and .bash scripting. I’ll admit, this course would have been much more difficult without the computer knowledge I already had.
I’m currently working full-time trouble shooting large 3D printers 40 hours a week. I’ve been pondering what to go to graduate school for. This course has helped with that decision. I’m leaning toward a masters in the applied data science.
I plan on taking the other data science and applied data science courses on Coursera as well. Any and all continued learning I can get will be valuable.
What was most challenging? Learning the syntax and structure of the python language. I’m still learning it and it’s going to take quite a lot of effort to master it. Attention to detail is an absolute must in programming or coding—albeit a short script or manipulating a data set.
Also, I found that the Anaconda suite was the best choice to complete the course. It was a little more user friendly than the bare-bones IDLE/Python combination.
By Courtney B•
I was a complete newbie to Python, and coding in general, and this course made it easy for even a beginner like me to understand. I would honestly love to take an extended version of this course. That said, I have recommendations for improvement:
1) the labs didn't really make you think terribly hard about how to solve the questions, and I would have loved more complex lab work, especially because of the next point...
2) The complexity of the final project basically skyrockets from the rest of the course work. I feel like an extra week or two of going over the additional knowledge necessary to really succeed in the final project without major struggle would help tremendously. Conceptually, it seemed like it should be REALLY easy... if only I had a little more applicable practice work under my belt before hand. (I finished it successfully, but it was a bigger struggle than it perhaps should have been. I think many other people are in the same boat.)
By Whale M J•
This action-pack course is exactly what I am looking for. It's down-to-earth and practical. Instructors explain with videos once, then you get walk through in the labs, like a step by step guide.
The videos are of bitesize length so it's easier to concentrate on the concepts., and followed by quizzes that ask only the essentials. i love the part that i can experiment with the code myself after researching the concepts further on the internet.
It may be pretty demanding for complete beginners because each concept is introduced very succinctly, so if you have no clue with python at all, i think you need to research extra a lot in order to understand the concept. There are also a few minor typos which may affect the understanding, just really minor ones like a becomes b while b becomes a, or some general english typos.
Perfect for those who want to get a taste immediately what data science looks like, like myself.
By Luis R•
Curso adequado tanto para completos iniciantes (primeira parte do curso) quanto para quem já conhece o básico e gostaria de conhecer e expandir seus conhecimentos nos módulos Pandas, Numpy e Matplotlib.
A parte teórica é apresentada com excelência em videos curtos de maneira bem direta e sintetizada, ideal para desenvolver um bom ritmo de aprendizado e de conclusão do curso.
A parte prática é montada de forma a possibilitar qur você aplique na hora exatamente o que acabou de aprender, acessando a plataforma após cada video por meio de links. Lá você vai encontrar exercicios simples e com explicações e passo a passo
O projeto final é simples, porém muito enriquecedor. Aplicando diretamente conhecimentos sobre os módulos aprendidos e códigos python na análise de um dataset disponibilizado e na geração de um dashboard de visualiação de dados.