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Learner Reviews & Feedback for Machine Learning With Big Data by University of California San Diego

4.6
stars
2,345 ratings
497 reviews

About the Course

Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: • Design an approach to leverage data using the steps in the machine learning process. • Apply machine learning techniques to explore and prepare data for modeling. • Identify the type of machine learning problem in order to apply the appropriate set of techniques. • Construct models that learn from data using widely available open source tools. • Analyze big data problems using scalable machine learning algorithms on Spark. Software Requirements: Cloudera VM, KNIME, Spark...

Top reviews

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!

PR
Jul 18, 2018

Excellent course, I learned a lot about machine learning with big data, but most importantly I feel ready to take it into more complex level although I realized there is lots to learn.

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326 - 350 of 478 Reviews for Machine Learning With Big Data

By KOUSHIK C

Dec 17, 2017

5/5

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 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.

By carlos f o

Apr 27, 2020

Un excelente curso, para aprender ML, y buenas herramientas, aunque el uso de Cloudera para Big Data es pesado para procesar incluso como VM. se refuerzan conceptos. aunque algunas veces si es bueno detallar algunas etapas como la normalizacion que es muy importante.

By Ahmed O

Oct 21, 2017

very good introduction to the topic. I enjoyed the hands on exercises but wanted more explanations and may be more reading/exercise and in depth to pyspark. Overall I would recommend this course for anyone like me just starting to scratch the surface on chine learning.

By Ahmed S

Mar 24, 2020

This course is really nice and interesting one. Dr. Mai is excellent instructor and has good capabilities to simplify complex ideas. However, I did disagree with the course name since a main subject of this course "big data" is not touched in the given sample dataset.

By Dhananjay W

Oct 28, 2020

Non working libraries are there in cloudera. I got lot problems to install jupyter and ananconda therefore I used my os and installed everything indivisually. Please solve that. Anyway other things are awesome. Good Job. Thank you very much for providing this course.

By Roman J

Nov 30, 2016

Have to make sure that code provided are fine and without problem... also, better instructions on how to go about the tool needed to use. Remember, we are learning and the amount of tools in Big Data ecosystem is vast...

By John C

Dec 9, 2018

Interesting material. Ran into several issues with the hands on that could have been avoided. Loved learning more about Neo4J. The section on Spark needed more time and additional descriptions.

By Carlos A

Feb 3, 2021

The course is excellent, the hands on allow are realistic and allow you to have contact with the analysis tools and real Big Data applications. I am very happy and satisfied with the course.

By Jürgen B

Oct 31, 2018

Reasonable overview. The VM environment is a major challenge for my hardware. Takes more time to make it work than it should. I am wondering if a cloud solution e.g. GCP would be better.

By Jamal A

May 10, 2017

Great overview about the machine learning in general. There are still lots not covered specially the Neural Network algorithms. Learning Spark MLlib was great advantage of this course.

By Tariq A

Dec 27, 2019

The fact that the assignments are graded means that there’s incentive to work on them, solve problems, and ask questions. Traditional online courses don’t offer that incentive.

By Dushyant

Sep 7, 2017

Hands n exercises and corresponding quizzes are great !Content could be more detailed, but may be I felt it so given my past exposure to ML. I enjoyed learning Knime and Spark.

By SUNITHA N

Dec 4, 2017

The precise definitions for many commonly used terms were very helpful. You do not find these details in many books or documents. Also, using KNIME was also interesting

By Santiago Z

Aug 23, 2020

Good course, but I found several problems in the virtual machine and it was difficult to solve them with the forum info. I had to rebuild the vm several times.

By Thomas H

Nov 27, 2016

Good overview of working with SPARK and KNIME - acceptable little theoretical background for all the presented concepts for the sake of application use.

By vishal c

Sep 12, 2017

This is a good course to understand how we can apply basic ML algorithm like classification, clustering using KNIME and Spark ML on very high level.

By Gustavo I M

Jul 3, 2019

Good, would be better if was in portuguese. and sometime is very painful configure the machine. But is a good course, better than the previus 3