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!
By Anton M•
Apr 28, 2020
A bit dissapointed by this course. The main topics were given clear and simple, but there were too few details, saying that all the details are out of scope of the course. But I would prefer to have more information and also more mathematical details (I find the argument that it needs appropriate background strange: if one wants to learn Machine Learning, should already have some basic mathematical background as knowledge of derivatives, integrals, etc).
Another big disappointment was absence of the graded programming assignments, except the final project. Every part of the course had just graded Quiz, but real hand-on scripting in python was given just as non-graded example, and then final assignment basically consisted from the same code.I find this approach quite useless. Also the final assignment had to be done at the IBM Watson website - I guess just for advertisement of IBM services - but this is useless to waste time on registering there, and figuring out how to do things there, if instead could be done inside coursera itself.
And finally, there few some mistakes and typos e.g. in the final assignment, which made everything a bit confusing.
By Oliver S•
Apr 25, 2020
I liked the videos, but there are a lot of mistakes in the notebooks, especially in the solution for the final assignment (which results in unfair gradings). Most of them were mentioned in the forums months ago, but as with all IBM courses, that I have finished so far, no employee seems to care. None of the mistakes gets corrected, and most of the time, you don't even get a reply from one of the moderators.
By Chang C•
Dec 08, 2019
I am very frustrated with the course's final project. Please, when you ask for tuning meta-parameters, either be specific or do not provide a false out-dated solution where there is no tuning at all in decision tree, svm, nor regularized logistic regression. Not every new-to-stats understands your misleading instruction of the final project or can be capable of grading according to what is actually correct.
The instructor should be more aware of this issue. I ask for a refund, it doesn't worth my money!
By Gilbert V•
Feb 07, 2020
Course is largely a scam. At the end you have to have a peer reviewed project that will prevent you from finishing the course if other people do not grade your project. You can have a high enough overall grade that you could get a 0 on the final and still pass and still be out of luck if people decide to not help with grading, which is exactly what happened to me. Do not waste your time and money if you want to be at the mercy of other people.
By Jim F•
May 03, 2020
Using IBM Watson Studio 'Lite' plan is a huge pain in the ___. I had to use 4 different emails to start from scratch to submit the notebooks for peer review. The course's instructions don't mimic the actual site - sometimes I wonder if they're referencing the same site in the instructions. You can learn this information elsewhere without added the headache.
By Ubaid M W•
Oct 22, 2018
In lab there are many funtion , libiraries Which have been used first time with out any description , then I have to search for each and every funtion or lib which is way time consuming which make this course worst courses in my list.
By Oritseweyinmi H A•
May 13, 2020
Great course! Get ready to learn, code, debug, sweat, learn some more, fix your code, then finally smile when your ML models work smoothly.
That last statement described my workflow during the final assignment/project of this course.
Quite simply, this course was brilliant because not only did it bring everything we've learned so far together but it also built upon the last course and properly introduced us to Machine Learning and its applications. In his videos, Saeed successfully breaks down complex topics into digestible byte-sized content and ensures that you intuitively understand what is going on.
One of the best pieces of advice I have received in regards to my learning and in life in general is to make sure you have a strong grasp of the fundamentals and these become building blocks to much more complex topics. That in a nutshell is what I believe this course has done for me.
To those who are reading this review, trying to decide whether or not to take this course... just do it! What are you waiting for? No seriously? This might be one of the best decisions you make this year.
If you've been racing through the other courses up to this point, I advise you to slow down once you get here and really try to digest what Saeed has taught here.
Watch the videos, pause, take notes, rewind, continue watching, learn, code. Iterate.
By Ugwu G C•
May 14, 2020
I love every bit of this course. It is very informative and the explanation by the instructor is second to none. He explained most of the concepts especially using real life scenarios like customer segmentation, detection of cancer and many more. Using these real life examples in the explanation made me understand the course very well and also appreciate machine learning. It will be very easy with anyone with mathematical background though people that are not mathematical inclined may have some difficulties understanding some of the concepts. Nevertheless, going through the lab section will make you understand the concepts very well even if you didn't get all the theoretical concepts. The final project was also centered based on what was taught and easy to follow by anyone that paid apt attention to the lectures and followed duly in the lab exercises. Kudos to the instructor.
By Kalpesh P•
Nov 29, 2019
I personally felt, it is one of the best modules offered as part of certification program. Data science has large number of algorithms, so naturally it is difficult to cover most of them and more importantly it is difficult to decide where to start from. Module is well designed, and it has provided basic to intermediate knowledge of most of machine learning algorithms, must to know for beginners. Few minutes introductory video on any given algorithm, followed an hour-long lab practice is really helped to understand algorithm and it’s implementation using python. Provided structured course really helped me to perform machine learning implementation using python. Great content to spent time on!
By akshay s•
Aug 09, 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 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 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 Iskandar M•
May 06, 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 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 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 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 Jaime O•
Apr 19, 2020
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
By William B L•
Mar 27, 2019
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!
By Christian C•
May 05, 2020
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.
By Timur U•
Mar 27, 2020
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.
By Juan R•
Sep 09, 2019
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.