The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.
I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.
von Juan D M G•
Me gustaron mucho los temas del curso! Los videos son buenísimos para entender la teoría; sin embargo, en los laboratorios no está documentado el código y hay muchísimas funciones nuevas que son usadas y no hay ninguna aclaración de cómo se usan o para qué se usan. Sólo en un laboratorio encontré todo documentado y explicado.
von Sven V•
This was by far the most time intensive course, not because the topic is so difficult but because the intructions for the final assignment are so vague and unclear. Otherwise the theory sessions were good. But whole structure of final assignment from definition all the way through marking is not clear and VERY time consuming.
von Lahiri B•
The course content is good. But final assignment needs updation. e.g jaccard_similarity_score is
deprecated. It needs to be charged in the notebook. There are less experienced candidates which get this wrong. And it is unfair. They are not expected to know that it is deprecated(That is not the course criteria)
von VIBHOR B•
The coding part should be explained as well. The autofilled code makes the learner lethargic and lazy to code himself. I;ve faced this difficulty and I cannot certify that I am 100% sure of what code I've learnt. Please take proper steps in order to teach CODING as well and not only theory.
von Amir H•
the level of the course was lower than I thought it will be.. especially comparing to the final assignment.
nevertheless it did give me a strong basic for most of the materials at least to the level I will be able to explain each topic to one who doesn't know nothing about machine learning.
von Mohamed M•
This course is a great introduction for people who have a background in Python and mathematics, but from a personal perspective, it should pay more attention to the details of the machine learning algorithms and special cases and do more practice using harder, more inconsistent use cases.
von LAURA T G•
Very demanding, that is great!!
It is not updated, therefore many instructions are incorrect and instead of 1 hour, one can use 2 or 3 days.
The system Watson Studio is not working all the time. I lost many lines in my final project because it stoped before I could save the changes
von Elvijs M•
The only OK course in the specialization. I found that the intuition/concept behind various algorithms was explained quite well. The mathematics, on the other hand, were basically skipped. And as always, the assignments are sadly pretty much "copy and paste from the examples".
von Samantha R•
Good course and quite relevant. However, the project was not gearing up for the final Capstone project. I did not feel the skills I gained from this course set me up to succeed with my Capstone project. I felt like I was still in the dark running any kind of machine learning
von Simon C•
Some of the material is out-of-date with respect to current versions of the Python libraries. There are a lot of typos in the material. In the final assessment, the instructions were quite vague regarding what information should be included in the submission.
It go through many kinds of machine learning with only simple sample. it doesn't seem like I can earn some job-ready skill after taking this course. The introduction is good, but the content are just too simple to help us deal with real problem.
von Mohammad Q•
It is an overwhelming course.. really it is packed with knowledge.. yet I with that in the video the instructor explain more in the code.. the theoritical knowledge is understandable but when coding comes.. things getting little bit difficult.
von Jeremiah T•
Explained basic methods of machine learning but could have provided more guiding information on the final project that encouraged learning and helped us complete the project efficiently but also compel us to explore the methods thoroughly.
von Bea C•
Loads of typos/spelling mistakes throughout, some contradictory statements in the quizzes that need to all be ticked, some questions are unclear... Overall the content isn't bad but the entire course needs to be spellchecked and reviewed.
von Joel M A•
Good survey material for those unfamiliar with statistical concepts, but the training material is incomplete, misleading, RIDDLED with spelling/technical mistakes, and only the forums address the methods to submit homework correctly.
von Andrei-Ionut D•
Not too many explanations for the assignment, only 2 rows which are supposed to tell us exactly what we have to do. This is why everyone ended up creating very different things, which made it harder when reviewing their work.
von Kevin C•
Great course but the final assignment was very fiddly with standard libraries not being uploaded properly in the Watson lab notebook provided. There was no option to use local environments to mitigate this. Hence 3 starts
von Adam J L J H•
I think that the Machine Learning Models taught were explained really well In theory to help understand what we are doing. However, there is not much explanation to the syntax of the models which could be elaborated on.
von Artin Y•
The course was very intense and it was not clear what was wanted from you(i.e. the scope you're expected to know for the exams)
The quizzes are vastly different from the final project and don't prepare you for it.
von Atharva J•
I got a great understanding of the concepts but, there should have been more videos related to the implementation(coding) part. There was just once use of Third-party tool for every module and nowhere else...
von Julien P•
Content was good, a bit shallow on some aspects (didn't cover many ML techniques, was light on SVM content, etc.). But the quizzes were too easy and didn't properly test technical aspects of the course.
von Mohammed A Q K•
The sections on Clustering and Recommender Systems were difficult to follow. It would have been ideal if they had more in-depth video explanations or if the contents in the lab notebooks was simplified.
von Shreya D•
It is a really good course for understanding theories and covers vast topics! The concept were explained very nicely but it lacked proper mathematical working of algorithms or deep intuition about them.
von SAIKAT B•
There is more theory than practical examples and exercises. The final project is nowhere near the actual course syllabus. No ML algorithm is taught in the course. But you ask them in the final project.
The instructor is very good and explanation of concepts is very clear.
But the code explaination is not there so we have to search for each keyword on google. Just wanted to have someone to explain code.