The process for learning in this course is throwing pieces of python at you with little context in how they would actually be used in the real world and leaving most of the practical labs to the very end. Doesn't seem this will actually help people retain more than 15% of what they've gone through.

The course generally explains concepts in a good and illustrative manner. The only thing I found hard to understand and wasn't demonstrated with examples is API. Furthermore, I suggest the quizzes and the lab exercises become more competitive and more advanced. The questions posed are very basic.

The exercices from week 3 to week 5 are too difficult. It would be really useful to have more exercices with a progression in it instead of one big exercises mixing everything.

The weeks 4 and 5 are really difficult to understand because there are a lot of new things explained really quickly.

Interesting introduction into Python, tools and some libraries. It's pretty easy though and i feel like once we reach the files management, Pandas and Numpy we should get some real exercice to practice and get confortable with those since they are super important for what are you aiming for.

In the course, some of the details were submerged too quickly without providing the basis. In other words, the structure and structure of the syntax was hardly dealt with, but they worked with it at the same time (at least in the videos). The course itself is suitable for the beginner level

Ok course for understanding the basics of python. Some exercises (week 3-5) didn't always seem to match the basic nature of the videos and were a bit frustrating. Because it's pretty surface level and the exercises didn't reinforce my learning, I felt like I walked away not learning much.

Course gives some general understanding of programming in python, but it is too condensed in my opinion. Sometimes materials lacked in consistency (strange lab .ipynb files naming, few of those were not working correctly). Definitely not enough to get to know such great language as python

The course content was good, but the hands-on labs were very confusing. It was not clear how to practically apply the knowlede. I did a pyhton course prior to this, bit for someone with no prior python knowledge, this must be very confusing. Better, more visual practicals would be better.

The videos are not nearly long enough for the labs. All the tools we need were not mentioned in the beginning, and the labs frequently are not complete or do not work.

This is not helpful for someone who is at the very beginning of learning Python because I dont know what to look for.

All Content of this course is Very Good, But one things is irritated which is the project submission using 'IBM Watson Studio', this platform can't loading easily it is time consuming and Slow platform for data processing. For this course we need a lite platform which is loading fast.

it is a baby class for coding while it is not very challenging and practical. the code is sometimes outdated and is done in a time-wasting manner. one of the biggest problems is that the course refrains itself from using other libraries which are frequently used or common in practice.

This course had tons of information that at times was overwhelming for someone without a data science background. I would have liked to see the course work split up a little more along with more introductory/overview lessons, like who uses Python, how is it used in the real world.

This course was frustrating because there were some issues with using the IBM cloud and they could not be solved quickly. As a result I comlpleted the course without completing all the practical exercises, so I missed out and did not get all the value I should have from this course.

This course does a good job of introducing the basics of python. However, the slides in the lecture videos are so atrociously formatted (and riddled with typos), that they have an annoying and distracting effect. Even in a high school presentation these slides would be embarrassing.

Good structure, learning progressively helps. Labs are interesting and allow to learn to code. Two drawbacks: 1) very unequal distribution of work, Week 4 was too long, while Weeks 1 and 2 were light; 2) a lot of mistakes in the course, up to the point of sometimes being confusing.

OK overall, but many links to external resources were not working and how-to screenshots often out-of-date for those services. The analysis side was a little light as too much time was spent on the intro to Python. It would have been better with Python knowledge as a prerequisite.

Good course but there were large gaps in information, plentiful typos, and confusing explanations. As someone who educates for a living, I'd say this should likely be broken down into more than one course and the materials should be reviewed for grammar, errors, and readability.

I really like the topic and overall progression however, Week 4 and Week 5 have serious issues with the pacing and the difficulty curve.

I also strongly feel that extra reading and practice on MANY of the topics would lead to better understanding and an easier time (later on).

There are a lot of code unexplained. I would've liked more videos explaining how to write a code bit by bit especially in weeks 4-5. the exams don't match the labs. Overall the course is ok but I can't say I'm capable of writing code like was shown in weeks 4-5. Thank you :)

This course was pretty hard for me who has no computer coding at all in my background. The beginning modules were a good start but to have to read code and write code was very frustrating to me. Great content but not really geared for a beginner; more intermediate learners.

the web scrapping part of the course was not taught right sadly I finished the course not understanding the process completely which is my first time to feel like this I hope you consider changing the mentor for the web scrapping part of the course and thanks after all :)

The course provides a massive amount of information in a short timeframe. It gets overwhelming quickly. I also needed to find other resources to supplement the course to get a comprehensive and functional knowledge base to understand the more advanced topics in the course.

the material and movies were good, response from teachers to questions was terrible (takes a long time or no answers at all). the gap between the items learned and the week 5 project was too big. A lot of new things that were not mentioned or discussed in the first 4 weeks

First four weeks are excellent. Last week looks like a rushed scramble of three weeks worth of material jammed into one, multiple errors, final exam had three questions that had various problems with them starting with being unfinished to answers not fitting the question.

First 3 weeks was good and a very fast pace python lesson. When reach week 4 all goes down the rail if someone has no background on data science. Very hard to know what to do in week 4. Don't recommend you to take this course if you have no background in data science.