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.

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.

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.

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.

El curso es excelente, ofrece una visión completa del aprendizaje automático con Python. Los módulos están bien estructurados y los ejemplos prácticos facilitan la comprensión de los conceptos. Muy recomendable. El curso es excelente, ofrece una visión completa del aprendizaje automático con Python. Los módulos están bien estructurados y los ejemplos prácticos facilitan la comprensión de los conceptos. Muy recomendable.

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.

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.

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

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!

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!

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.

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.

Its a nice course for beginners! Gives clear explanations on some of the basic concepts! Python Notebooks give clear picture on basic code implementation aspects.

Suggestion - Week 6 there are 2 videos that need an update on logging into Watson Studio. Need to update the instructions with latest version. Its a minor correction; good if updated as our screens and options differ from your instructions.

GREAT CLASS !

IBM WATSON "JUPYTER" NOTEBOOK WORKED OUTSTANDINGLY WELL!

LEARNING FROM THE NOTEBOOKS IS AN IDEAL WAY TO LEARN THIS !

LECTURES ARE CONCISE BUT VERY CLEAR.

I FOUND MY PREVIOUS LEARNING/EXPOSURE TO MACHINE LEARNING VERY HELPFUL TO ENABLE ME TO ASSIMILATE THE (QUITE EXTENSIVE) MATERIAL!

MANY THANKS TO THE INSTRUCTOR AND TO IBM !!!

MANY THANKS TO THE INSTRUCTOR AND TO IBM !!!!!1

Course was great, however I think that when you deal with certain topics peer to peer review is not the best method for evaluation, or at least it should be kinda different from previous courses. In my opinion many students misunderstood some parts of the final assignment, so how are they suppose to review other's work? I saw I wasn't the only one noticing and having trouble with that.

Absolutely knowledgeable and interesting course with a plethora of insights and plenty of hands-on lab sessions to digest what you learn. I take this moment to thank all the resource collaborators and appreciate the immense effort they all have put into this course to keep it updated and attractive. I wish they could keep this up to help thousands of individuals to groom individually.

This course gives a good introduction (theory and applied) to a variety of machine learning methodologies. The presentations are well thought-out. The labs are great. I learned an enormous amount from doing the hands-on work in Watson Studio/Jupyter notebook.

This would be a bit much for a beginner in Python, but with a modest understanding of the language, this offers a lot!

Excelente curso. Los contenidos se presentan de forma facil y comprensible. Hay un gran dominio por parte del instructor y ademas, los contenidos son cubiertos con suficiente profundidad.

Excellent course. The contents are presented in an easy and understandable way. There is great mastery on the part of the instructor and also, the contents are covered in sufficient depth.

I really enjoyed this well-organized and professional course. I would like to show my appreciation to the manager of this course, especially for a video presentation for each module. The technique to have Query and then Solution is the outstanding feature and helped me to cover all course materials and implement the Assignment tasks on a high level. Thank you so much.

This is my first Machine Learning course so definitely I've learned a lot of new things. You cannot associate 100% Machine Learning with Programming, Math or Stats. And even you use scikit-learn it's not enough only to read the help for this tool. You need to know what model fits your problem, how to interpret the result and how can you optimize the solution.

This Course is awesome to learn the theory and practice of some Machine Learning Metods.

By the end I feel like I can tackle my own datasets and analyze them with various methods seeking the optimal one.

The only thing that could be better is if the course could go a bit deeper into the optimization algorithms (like gradient descent) even if it's a bit mathy.

[PT-br] Um dos melhores cursos onde se alinha teoria com a prática na área. Conteúdo bem completo, passando pelas diversas técnicas de ML, com vídeos muito bem explicados e conteúdos práticos que demonstram como aplicar cada técnica. Além disso, as provas são bem desafiadoras e o projeto final é bem completo, o que aumenta o valor do certificado ao final.

No Doubt COURSERA is always best AND MNC like IBM,Google courses associated with coursera are MIND-BLOWING.

The Instructors are so great at Explanation Part that hardly anyone won't Understand All the Topics

I would love to thank all the INSTRUCTORS who created such a Awesome Content for us.

My Personal Ratings For All the Instructors: 100 / 100

Thanks! to Coursera and IBM.

As a beginner i had learn lot about machine learning in practical manner.I want to appreciate IBM skill network team for these wonderful course.In these course all the topics are explained in practical way.

Thanking You