JG
Oct 24, 2020
Excellent course. It teaches the basics with a great method and with practical exercises, involving real data. The sctructure is clear and it covers a good amount of topics. Well done San Diego!
PT
Jan 8, 2017
The course was the best introduction I had for machine learning. Helped me a lot to understand different concepts from people who already know about the subject and I didn't have any idea.
By RAGHUVEER S D
•Jul 25, 2020
good
By VISHNU T B
•Jul 11, 2020
Good
By Rabindra k S
•Jul 7, 2020
good
By Prof. A
•Jul 1, 2020
Good
By SURAJ P
•Jun 15, 2020
good
By vanusha
•Jun 5, 2020
good
By Mosfiqun N H
•Jun 2, 2020
Good
By Dhananjai P
•Mar 27, 2020
Good
By Bhoopal
•Feb 26, 2020
Good
By Suriya B
•Dec 6, 2019
Good
By Priyanka
•Apr 29, 2019
none
By selvaraj
•Mar 21, 2019
good
By Fhareza A
•Sep 9, 2020
wow
By SHAKTHI S
•Jun 2, 2020
Gud
By KOUSHIK C
•Dec 17, 2017
5/5
By Shilpi G
•Jan 21, 2022
NA
By Jeffrey K
•Nov 9, 2020
There were several issues running the hands-on assignments; problems with getting various python tools and/or features. These issues made the labs frustrating at times, take much longer than needed, and quite stressful to complete.
This is an old specialization and must be updated with a variety of necessary modifications done to it in order to keep it running!
By Jose J H G
•Apr 26, 2020
Se abordan conceptos teoricos muy importantes pero el uso de pyspark en algunas oportunidades es complicado ya que no se da una introducción al tema, por lo q se da por sentado que la persona que hace el curso debe conocer pyspark. Adicionalmente me parece interesante instalar pyspark en mi propia maquina sin tener que usar una Maquina virtual de cloudera.
By Jose F Z R
•Jan 20, 2017
Good overview of tools specially Spark. The last demo handson with Spark clustering had too much content to be covered in 11 minutes. The presenter does not give any details on many functions he was using. Felt like copy paste coding. The rest was good, specially the lecturer compared to the lecturers of the other courses of the specialisation.
By Gail H
•Feb 18, 2021
Lot of problems with setting up the virtual machine initially, but these can be resolved by doing the exercises on your own local computer instead. The exercises are great! Very fun exposure to ML libraries. I found myself using sci-kit libraries instead of the Spark libraries to complete the exercises, and it worked out just fine.
By Ramya S
•Mar 3, 2018
The entire coursework is very well explained and organized such that we will get better understanding of the terms related to this field. Hands-on exercises have also given better insight of how to use those tools. I would suggest to take this course for getting a brief knowledge about Machine Learning and Big Data.
By Juan E F A
•Apr 27, 2020
The content of this course is very useful. I really enjoyed it. The only problem I had was the possibility to work with an instance of Apache Spark in my laptop. This machine couldn't initiate the instance because of its capacity. I think they should recommend other online utility for the hands-on practices.
By Tanver A
•Apr 20, 2024
These are very effective courses with hands on practices that will give you a deeper understanding. However, the VM tools are outdated. These do not work, so you have to workaround for the alternatives, if you dare to take the challenge of completing this course ;). Happy Learning!
By David L
•Sep 28, 2020
This course is probably a little bit too simple for anyone with a basic background in machine learning. The introduction to KNIME was unexpected but a nevertheless welcome addition. The Pyspark course material could do with updating to reflect changes in a few python libraries.
By Ravisankar S
•Dec 16, 2019
Only one concern that was faced during the course is, unfortunately, all the needed spark related libraries are not available to setup. It would have been nice, if either online compilers or readily accessible along with the course, would have become learners journey smooth.