Feb 07, 2019
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.
May 26, 2020
Labs were incredibly useful as a practical learning tool which therefore helped in the final assignment! I wouldn't have done well in the final assignment without it together with the lecture videos!
автор: MICHAEL K•
Sep 16, 2020
The Machine Learning course was made practical with hidden mathematics and applied to solve real world research problems. The instructor merged the theories with labs to simplify difficult part of Machine Learning. I recommend this course for any one interested in using predictive modelling to solve research questions.
автор: kalidindi s v•
Apr 04, 2020
Before joining this course I thought ML is so tough. But after this course I got a overview of some of the concepts of ML and not only overview, they also provided the lab sessions for every concept they teach. I suggest the beginners to join this because they get the complete overview of Machine learning. Thankyou..
автор: Rafael A C•
Jun 24, 2020
Presentations are very well designed. I have teaching experience and I can tell you that my style is great for illustrative purposes.
I learned to conceptually understand the mechanism and purpose of the models presented in Machine Learning. I feel like I can do things that were unthinkable for me before. Thanks IBM!
автор: Abhijit S•
Mar 09, 2020
This introductory course is really very good to understand the basics as well as methods to perform activity. Would recommend highly to anyone wish to learn ML in Python. The explanation, bit of maths and code were flawless and explained well in video as well as in code (most of code is explained in sample notepad).
автор: Daniel K•
Nov 01, 2019
The information in this course is laid out in a easily digestible format that makes it possible to fully own the knowledge that you gain and put it to the test. I appreciate that the videos are straight to the point and that the jupyter notebooks illustrate varying techniques for cleaning data. Tremendous value.
автор: Amy P•
Jul 25, 2019
Having worked my way through the IBM Data Science courses, this one was the "pay off" - it was so cool to finally apply more sophisticated techniques to real world data sets. The labs were fantastic. Highly recommend this course to anyone interested in learning about the most popular machine learning algorithms.
автор: V M R•
May 18, 2019
Complex concepts of machine learning algorithms are explained clearly with an illustration. Learner definitely have confidence in Machine learning after this course completion. A practical assignment work is really helped the learner to do the implementation of classifier model of their own and gain confidence.
автор: Shakshi N•
Jan 15, 2020
This course has been awesome. I have been doing ML Work for my college for quite some time, but never understood what goes in it, and kind of surfed through the net and just did the work. But this course has given me in depth knowledge of the logic that goes behind these algorithms and for that I am very glad.
автор: Mayank P•
May 21, 2019
This course offers a simple and effective experience. I learnt how to find the most accurate algorithms in the scenarios. Most importantly, the Jupyter notebooks provided are although optional, but you should study them thoroughly. They might seem difficult on an overview, but are very easy to understand.
автор: Surendrabikram T•
Jul 13, 2019
It could be even better if programming assignment were provided in each week but still, final assignment was of great quality and I found it really engaging. The program introduces you to scikit learn which is again a wonderful advantage of taking this program. I am giving this course 5/5.
автор: Li G•
Aug 26, 2020
A very good course for beginners. It's quite practical and helpful. If it can go to more details of the machine learning modeling algorithms, it would be better. I get an overall picture of simple machine learning tasks but cannot handle real work task yet. The real world is much more complicated.
автор: Christopher A B•
Aug 19, 2020
The course was quite challenging. I especially appreciate how the labs required significant modification and deep understanding of the underlying motivation for the code in order to complete the final project for the course. Thanks to the lab authors and instructors for some high-quality demos!
автор: Luis M•
Jan 08, 2020
The course was thorough and a great introduction to machine learning. The capstone project was challenging and required me to have a good working knowledge of the various models. This has been the most intensive course, so far (course 8 of 9), in the IBM Data Science Professional Certificate.
автор: Priyansh S•
Jul 20, 2019
The course is really good for machine learning beginners. I would recommend everyone to take this course as it gives you all the basic knowledge and working of ML. It is fun to do with the Jupyter notebook tool which gives a great actual experience. Thanks a lot. This course helped me a lot.
автор: Srikanth G•
May 07, 2020
It is indeed a very thorough course, yet easy to understand. The animations and visual graphics made it an engaging and pleasurable experience. Learning classification, clustering and regression was made easy in such a way, that I could do it all over again without hesitation. Keep it up!
автор: Jeffrey P•
Jun 17, 2019
I think it would be beneficial to talk about neural networks somewhere after the gradient of steepest descent section. I did appreciate the course talked about many other ML algorithms that are not typically covered by other programs - and the lab notebooks are extremely valuable.
Apr 17, 2020
If more knowledge on 1) how to find the optimal depth value for decision trees and variables for other models; 2) explanations on parameters used, will be elaborated in hands-on lab notebooks, it would be better. Those are important to new beginners with zero idea on ml models.
автор: Yi Y•
Oct 03, 2018
It is one of the best introduction course to Machine Learning.
The material is well explained to someone with a beginner level of understanding to Statistics and Machine Learning.
All the material is presented in a way that is easy to understand, without leaving out the details.
автор: Shiva S•
Mar 19, 2020
This course is a good chance to start python programming and reviewing ML concepts with deeper insights. I would suggest it for those who are familiar with ML and its algorithms. For those ones who want to start learning ML, it is better to take ML courses with Basic level.
Nov 27, 2019
Great course, cover many important aspects of classical machine learning algorithms. The lectures are very focused and not tedious. Labs are excellent, and can serve as a starting point for every data science project in the future. I definitely recommend taking the course.
автор: Pankaj Z•
May 03, 2020
This is one of the finest courses for anyone who wishes to transform his/her career into Machine Learning. It has optional external tool assignments after each chapter to help you understand and try out code and the concept. I would highly recommend this course to anyone.
автор: Dominique D•
Apr 16, 2020
If you put your heart to it, there is really a lot to learn in the course. The course touches quite some ML topics and gives a good introduction to it. I feel I got a whole new set of tools to use, and i am hungry to learn and experiment more.
Really enjoyed the course!
автор: Benedict A•
Apr 02, 2020
The videos and labs were remarkable in that it was able to concisely communicated vast and complex information.
I did have to do additional research to fully understand and appreciate the material because I am not coming from a programming or statistical background.
автор: Toan L T•
Oct 28, 2018
Knowledge wise, just like Prof. Ng's, minus the mathematics foundation.
Practical wise, carefully designed labs really help learners understand the data cleaning processes, understanding data through visualization, ML algorithms and evaluation metrics.
автор: Roger T•
Mar 28, 2020
It's a very precise and practical course. It focuses on the main ideas and application aspects of M.L., without drilling too deep into the math rationale behind.
To get the most from this course, it's good to equip yourself with basic knowledge in numpy and pandas.