The course was amazing to get started with machine learning. You are going to learn about some amazing machine leaning algorithms and for the capstone project you have to use them to find best accuracy for a dataset. Peer reviewed assignments are really good as they help every student to know different techniques each person use and can learn from them.

Great introductory course. Clear explanations and good homework to get your hands dirty and see results of algorithms.

A rather minimal mathematical understanding is assumed by the course so begginers would not be overwhelmed.

Keep in mind this course will not make you an expert or teach you how to write some of the more advanced algorithms by yourself.

Excellent Course. Course cover.

1) Regression

2) Classification- Algorithm :KNN , Decision Tree , SVM , Logistic Regression etc.,

3) Clustering- K-Means , Hierarchical ,Agglomerative ,DBSCAN

4) Recommender System - Content-Based and Collaborative Filtering

5) sci-kit learn and SciPy details with Practical labs on Jupyter Notebook on IBM Watson Platform

This is by far the best course on ML. I have explored many online courses. However, this one is the simplest and most effective. Instructor (Mr. Saeed) has explained the concepts with practical examples. His way of explaining things is very simple and to the point. I enjoyed each and every section of the course. Looking forward to his next course.

JupyterLite is encountering issues when it comes to handling lab assignments, while Jupyter Notebook is performing very well. Consequently, when lab assignments require verification or work, the online lab using JupyterLite fails to function as expected. The problem appears to stem from the incomplete or unsuccessful installation of libraries.

The Video content is very clear and simple to understand the concepts and lab is very good. The IBM Trainer

SAEED AGHABOZORGI

did a great job in this course. Got hand on experience on Machine learning. Final Project is helpful to apply all the concepts I learned throughout the course. Glad to get this certification from Coursera and IBM.

under well designed syllabus , became easy to learn and solve real world examples,which keeps motivated through out the learning process . The fascinating about this platform is the ease for access to quality resources or otherwise it is difficult. The end of course meant to me s skill for solution to many issues irrespective of field.

This is an excellent course for a quick review of what you know about Machine Learning.

I think you should mostly know about the basics of programming in python and also Machine Learning, but this course gives you a great quick review and also is an excellent example of python machine learning tools.

I strongly recommend this course.

A nice and quick overview of how the main machine learning methods work and how to apply them by means of the python library Scikit Learn. It does not dive too much into the details, but explains the main ideas clearly and provides you with the main python routines to use ML on real data.

Recommended if you are new to the field!

This course is one of the best course i have taken on coursera, it not only treats you as a beginner but also provides the detail technical details so that one can learn more on his on. The lectures are clear and quiz are tough, Labs give a thorough overview of each topic. I would like to thank you the instructor for his effort.

One of the best courses in this certification.

The best part of the course is the labs.. very well structured.

In this certification so far, the machine learning with Python (course 8) and visualization with python courses (course 7) are the best

The assignments are good and there is very little 'spoon-feeding' so its more fun.

This course is truly GREAT. I had never dreamed of being to understand what it means to do machine learning as I do not come from a computer science background. In my part of the world, even graduates have so great a problem with technology and I am just so happy to have my hands on this course. The lessons are invaluable.

Thanks for providing this excellent course. It explains things clearly and step by step. I learned a lot from this course. There are some minor errors in the exercises. It would be good if the team updates the exercises codes more frequently. And it would be nice if we will have a standard answer for the capstone project.

Brilliant content for starters like me who are looking to make their way into the Data Science world. The course offers a conceptualised learning experience with practical examples to enhance one's skills. I loved the content and the instructors are very fluent. A great course for anyone looking to enjoy introductory ML.

I have found this course very helpful - in terms of the concepts explained in the video for the different machine learning algorithms.

IBM Watson studio is very useful tool introduced through this course.

The assignment notebooks had guided instructions - on how to apply the learnt coding techniques and various ML models.

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.

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..

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!

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).

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.

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.

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.

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.

Amazing course... !! Thoroughly explained every concept with a number of examples.Also helped me to remember the concept by quality test at the end of every topic.It also helped me to learn more about the concept by applying those concepts in the real time projects.

thanks a lot for this amazing course...

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.