HV
Nov 10, 2024
With my background on probability and statistics, I think this is a good course, where it can help me apply what i have learned. Not recommend for any one who hasn't taken a statistics course before.
AE
Sep 26, 2021
Very detailed course of Exploratory Data Analysis for Machine learning. Ready to take the next step in data science or Machine learning, this is great course for taking you to the next level.
By Naveen G
•Aug 25, 2022
Content is good but teaching can me more better.
So next time please hire a good teacher.
By Busola A
•Mar 29, 2022
The videos are not well explanatory enough.
By Rakesh M
•Mar 12, 2023
Items not properly explained
By Raed A A
•Jun 29, 2024
it is to long!!
By ROHAN W
•Jan 19, 2025
very nice
By Upendra J
•Dec 3, 2022
jjefesf
By Sam R S E
•Jan 16, 2024
good
By Pavani P
•Dec 6, 2023
good
By Max M
•Sep 7, 2023
One of the most significant drawbacks of the course was the instructor's reliance on slides as a reading tool rather than a teaching aid. The slides presented the information in a rather static and passive manner, which made it difficult for me , to engage with the material effectively. Instead of actively demonstrating the application of formulas and concepts, the instructor merely read the text on the screen, leaving us to decipher the practical aspects on our own.
This approach posed several challenges. First and foremost, it hindered our understanding of the material. Exploratory Data Analysis (EDA) is a hands-on process that requires practical application, and it's crucial to see how formulas and concepts are applied in real-world scenarios. Unfortunately, the course did not provide sufficient guidance in this regard.
Moreover, this teaching method made it challenging to maintain focus and engagement throughout the course. It's difficult to stay engaged when the instructor's presentation primarily consists of reading text from slides. It would have been much more effective if the instructor had actively demonstrated how to use the formulas and provided examples that allowed us to see EDA in action.
To enhance the course and improve the learning experience, I would strongly recommend that the instructor adopt a more interactive and practical approach. This could involve incorporating hands-on exercises, real-world case studies, or live demonstrations of EDA techniques. Providing opportunities for students to actively apply what they've learned would undoubtedly lead to a more engaging and effective learning experience.
By Oleg O
•Mar 25, 2022
This course is too surface. You must have a solid background in statistics and be familiar with pandas/numpy python libraries, otherwise you will spend a lot of time just to learn these libs. Also there is some basic info in lectures but assignments contain much complex and harder tasks which were not discussed in the lecture. And the tasks already have answers , so there are questions and solutions in one place, it is very weird and annoying
By Chris R
•Apr 15, 2023
Note enough exercisese. In fact there really were almost no exercises, except in the Honors section (the optional 5th week - a peer reviewed project).
Lectures were too fast and not always clear. Ambiguous language was frequently used. I believe the instructor does know the subject, but there is too much glossing over. Going to look for a better class with more exercises and clearer definitions.
By Stephen C
•Jan 3, 2022
Frankly, the presenter is a poor educator and the course materials are weak. The examples are limited, some explanations verge on incorrect (description of p-values), and several of the graded test questions are ambiguous and encourage rote learning of the teacher's preference/positions, rather than testing the underlying concepts. I expect better from IBM.
By Mpho M
•Dec 1, 2020
Course videos are way too long.
No Jupyter support, so for the coding exercise one has to download the notebooks and either use Google Colab or locally installed Jupyter notebook.
By Sayan M
•Feb 25, 2023
The explanation from mentor in this course was not that great. It felt like he was just reading some lines from an script, rather than explaining in simple terms.
By Walter B
•Jun 14, 2021
The course starts well. Then it goes to statistics and not so much to machine learning. The assignment is not so geared towards machine learning.
By Agban o
•Sep 1, 2023
the lecture seemed difficult to follow. i wish things where better explained. had to go back and take some other courses to enable me catch up
By basilis s
•Apr 8, 2024
Not a very good understanding of all the concepts. The tests had concepts that weren't explained in the videos correctly.
By Yazan K
•Aug 21, 2024
the instructor didn't actually explain this course very well and I find it too hard to to understand a lot of things
By Arshad R
•Jul 9, 2024
Very vague - Un clear instructions - hard to follow - hard to understand the speaker.
By Shahbaz A K
•Oct 5, 2023
Does not cover basics in depth or with any clarity.
By Carlos M
•Jun 6, 2024
Se explica con poca profundidad cada tema
By HAMZAH A
•Dec 27, 2022
Not explained very well
By ValidaR
•Dec 19, 2024
Lack of information
By Zahra B
•Jan 1, 2025
This course was a challenging experience, and I struggled to follow the instructor. The quality of the content was poor, with numerous references to unclear terms that were not explained adequately. The instructor mostly read directly from a presentation, adding little to no additional value. Without studying the material elsewhere, I would have been unable to grasp many of the concepts introduced. Overall, it was a disappointing experience, and I cannot recommend this course. Please, IBM, take the time to review and improve this course to ensure it meets the standards learners expect.
By Hannan A
•Feb 27, 2025
I have wasted my time and money. In this course an instructor just come and tell the topics name and nothing important (just waste your time). Its my advice to those who wanna join that please dont