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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
15,242 ratings

About the Course

Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning. This course will begin with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more. You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression. You’ll also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN. With all the many concepts you will learn, a big emphasis will be placed on hands-on learning. You will work with Python libraries like SciPy and scikit-learn and apply your knowledge through labs. In the final project you will demonstrate your skills by building, evaluating and comparing several Machine Learning models using different algorithms. By the end of this course, you will have job ready skills to add to your resume and a certificate in machine learning to prove your competency....

Top reviews

FO

Oct 8, 2020

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.

RC

Feb 6, 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.

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101 - 125 of 2,667 Reviews for Machine Learning with Python

By Ahmed S

Oct 18, 2020

Certainly a great course, clear voice and visuals in which the concepts have been explained clearly with rich details. I have noticed many are complaining about the math, lab, coding and the conceptual explanations; so here is a reminder than the course strongly suggested a 'background in Python programing language' in the beginning. Additionally, this is an 'intermediate/ advanced' course for engineers and data scientists, so a well-established knowledge in math should've been already acquired by default, even though the math needed here is very basic and can be done automatically. Also, understanding the conceptual part is very important to perform tasks correctly.

By akshay s

Aug 9, 2019

I am thoroughly enjoying the course. The codes written are the shortest possible codes but the narrations are just fabulous to comprehend and remember. I need more practice to write the codes correctly by my own but my fundas are all cleared and I know exactly why am I doing the next step. 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.

By Nima G M

Oct 4, 2020

This is a Perfect course, except for the name of the course. It is one of the perfect courses for those who wanted to become familiar with different machine learning algorithms (different classification algorithms, as well as different clustering algorithms). In fact, it is the course I definitely recommend for those who want to start machine learning. By the way, I did not understand why the author used this title for this awesome course, given that he is not used Python programming. The best title might be this one, I guess:

"Different machine learning problems, and algorithms "

By Eirwyn Z

Mar 22, 2022

It's very basic but essential to understand more complex topics regarding machine learning. The Course is well-structured with good presentations. The only issue that I've encountered is with the IBM Watson Studio. For some reason, it just refuses to accept my credit card (which I'm currently using to pay for my other stuff) and boots me off the website every time. I create a GitHub repository for the final project and, fortunately, people have no problem reviewing my notebook on GitHub which allowed me to get around with the issue with IBM Watson Studio.

By Tushar S S

Jul 15, 2020

This course is perfect for beginners. It gives a basic idea about clustering, regression, decision tree, recommender system, classification algorithms along with Labs. You should know a little bit about Python programming and few libraries like NumPy, pandas, sciPy, and sci-kit learn. The Labs are great because you will be using the concepts learnt in the video lectures on the sample datasets and when you see the results, it will motivate you to go for some hands-on projects from Coursera Rhyme Project Network and it will be beneficial for you.

By Md. A M

Jun 13, 2023

I recently completed the "Machine Learning with Python" online course and I highly recommend it. The course provides a comprehensive introduction to machine learning using Python. The content is well-structured, the explanations are clear, and the practical exercises enhance understanding. The instructor is knowledgeable and engaging. The emphasis on practical implementation and model evaluation is a major plus. The course is user-friendly and allows for flexible learning. Overall, a fantastic course for anyone interested in machine learning!

By Sri K P

Apr 14, 2019

This course is an excellent platform to understand the basics of Machine Learning with python. The lab tools pioneer a way to understand the code and implement it. The videos are crisp and clearly mention the scope of the course which creates a curiosity to know more. However, the peer graded assignment is not an efficient way as 'sample notebook" paves the way to plagiarism. The peer grading also restricts the user creativity to write a simpler code as it may not be understood by other peers. Overall I am very happy with the course

By Om S

Apr 10, 2023

I absolutely loved the "Machine Learning with Python" course by IBM! The practical labs and concise, explanatory videos were a real highlight, covering a range of supervised and unsupervised learning algorithms, including regression, classification, and clustering. Learning metrics such as accuracy, precision, recall, F1 score, MSE, RMSE, MAE, and log loss, as well as gradient descent and cost function explanations, was particularly helpful. I also appreciate the quizzes, which helped me to check my knowledge.

Highly recommended!

By Christopher S

Jan 14, 2020

Excellent content and relatable use cases. As a beginner in data science with no formal programming, the information is presented in a way to help you understand the fundamentals and then apply them using the pre-built python packages that are widely available. I started with data science 3 years ago and it was very difficult to get started without any programming or statistics background. This course does a tremendous job of making it accessible, understandable and quite frankly a lot fun in the process.

By Gizachew A

May 20, 2023

I wanted to thank you both for the wonderful Machine Learning with Python course you have created. I found the course very informative and thought-provoking. I learned a great deal about applying machine learning techniques to data science projects. I really appreciate the way you presented the course and the real-life examples.

Thank you for giving me the opportunity to expand my data science skills. It was a pleasure taking your course and I look forward to learning more from you both in the future.

By Aniket A

Oct 9, 2020

This course is fantastic, It has adequate amount of theory supplemented by labs. I also like the Watson Studio, and the fact that you actually learn to use some industry level tools in this course really takes the icing on top. The staff is supportive and wonderful, the community and cohorts are great. Overall I would happily recommend anyone who has absolutely no knowledge about Data Science to start right here with this course. Really enjoyed and thank you IBM for you digital badge. :-)

By Oleh L

Aug 20, 2020

Well structured course, which will give you understanding of the applied way of working. The topics are explained in quite enought details, allowing you to use learned approach in practical way.

What I would personally wish - a bit more examples of different kinds. It should not be included into main structure of the course (to decrease a work load of Instructors and Students). It needs to go into Optional part, but I'm sure - who is interested in, will finish the task.

By Iskandar M

May 6, 2019

This course needs basic knowledge on algorithm and programming experience. I really recommend this machine learning course for those who have computer science, statistics, or math background. The instructor is very clear, concise, and using simple diction when explaining the subject. All presented in here is valuable and worth reading and listening. The final task is somewhat challenging, but we'll have to really dig into the examples presented in the labs. Thank you!

By Peter P

May 20, 2020

This course was perfect, especially in my situation. I know all of the math behind neural networks, and fitting, but there were many algorithms I've never been exposed to - and this course exposed me to a lot! I liked the hands-on coding labs and learned where to find a lot of Python stuff that I wasn't aware of. A lot of terminology that I'd heard about is now clear in my mind. And the amount math was balanced perfectly with the getting things done.

By Peruru S S

Dec 11, 2019

I really enjoyed taking this course. The instructor is to the point, crystal clear. Nicely explains the essence of the topics in 5 to 6 minutes. I recommend this as a good introduction course to get a basic overview of different algorithms. However, if one wants a deeper understanding with specific details, this is not the course. This course will definitely serve as a good introduction which help us to get motivated to do more advanced courses.

By Ashit C

Jul 31, 2020

I really enjoyed during this course . Gives you a lot of skills of how to deal with data ,predictions or recommendations. At the end i know how day to day life works based on machine learning as they quite kept few real world examples while explaining. Little bit of difficulty i faced while doing main project as there was less guidance on what we have to show at the end of project. But it was a great course. Worth spending time over it.

By Clarence E Y

Apr 22, 2019

This course will challenge learners to commit to learning about the key objectives for using algorithmic approaches to answering important business questions using data. The lectures cover the theoretical foundations of the "relationship" algorithms used for classification and clustering methods. Additionally, the labs provide a fully integrated environment in which learners can do hands-on investigations to gain proficiency.

By Dr. M C

May 30, 2021

The course was enlightening. The course is very well designed in terms of ease to follow from one to the next step. Concepts are well described along the way. There is plenty of room to try out different models and learn the next piece of the puzzle. Everything falls in place when you finally reach the capstone exercise. I recommend this course especially to those, like me, who love numbers! I enjoyed the course very much.

By Haroldo D Z

Sep 30, 2019

Hay un nivel de Detalle en los Algoritmos de Machine learning, que ayuda a entender como pueden aportar realmente en diferentes problemas de regresión, clasificación, clusterring y recomendación. y la plataforma es muy practica para lograr entender como un lenguaje como python puede aportar a hacer mas sencillo la aplicación y uso de estos sin necesidad de instalar herramientas ni conocer los detalles del lenguaje.

By Niladri B P

Jun 22, 2019

A lot of ground is covered here. So it won't make you an expert, but will provide a great base from which one can build further expertise. The videos explain the concepts very nicely, so it is important to sit, listen and take notes. The labs are also very detailed and occasionally a bit advanced with the code. Overall, however, the course makes you work but you can choose how much work to put into it. Recommended.

By Aaron S I

Jan 2, 2022

Good course. Has bits and pieces of heavy theory and practical application.

Final project is much more open ended compared to others in the IBM Data Science Specialization track so far. Multiple ways to go about solving the project, and yet most of them will work. Still a bit of hand holding to guide someone along as to 'what to do'.

A decent course to make sure you are well on your way to doing data science

By Zeynep A

Aug 21, 2022

This is the best course I've taken from coursera so far. I've taken courses towards completion of biostatistics certificate from Johns Hopkins and data analytics certificate from Google. However, I've found this course way better than others. Every second of the course was full of valuable information and the hands on projects were very helpful in teaching the material. I really enjoyed it and learned a lot!

By Hussain A

May 17, 2020

The best direct-to-the point instructor so far! After going through the major classes available on the net I found Dr. Saeed Aghabozorgi concise way of keeping videos short with no code and rely on labs with best example for each concept highly admirable in an intermediate course. It took me once 30 minutes for taking notes about a 5 minutes video, well worth it. I say keep it concise it becomes a reference!

By Andréas V J

May 16, 2020

Fantastic course for quickly understanding the basic categories of machine learning algorithms and how they work. I would recommend this course to those who have some experience in computer science or software engineering with little-to-no experience in machine learning. Covered in this course: machine learning basics, data regression, classification algorithms, clustering algorithms and recommender systems.

By Rhea A

Aug 29, 2021

The intuitions behind the algorithm were very well explained, however line by line explanation of the codes could have been provided. Thank you for the crystal clear explanation of the intuition, really helped me a lot in understanding the concepts. I will high recommend this course to the beginners due to the clarity behind working of algorithm it gives. Thanks a heap. Looking forward to more such courses.