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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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426 - 450 of 478 Reviews for Machine Learning With Big Data

By SELMI A

Apr 14, 2020

good

By Saravanan

Mar 28, 2019

Good

By Praveen k N

May 5, 2017

good

By AMIT B (

May 13, 2021

.

By Agaraoli A

Feb 10, 2017

-

By Hendrik B

Feb 21, 2018

It's better than the other courses of this specialization, but still I wouldn't say that the course is particularly good. Also, the instructors don't appear to care for the learning progress of the learners. There is next to no help via forums, for example. What I think was good is that the instructor attempts to explain the algorithms of the machine learning methods visually and comprehensively.

What I think is a joke is the way the quizzes are organized. The questions almost never deviate from a 'change a number or copy the code' style. Like this, you do not really learn anything instead of copying code and changing something. The quizzes need some additional parts where it is important to apply what is learned to new contexts. ADditionally, the instructors need to put more focus on explaining what certain parts of the code do and why certain parts of the codes are improtant- Otherwise, this course won't be worth more than learning by doing alone.

By Riccardo P

Jun 1, 2018

Not so happy... it would be a little bit better if I attended this one before the ML course by Andrew NG...

Here, the topics are just introduced and poorly demonstrated using Knime and Spark.

Maybe, I had wrong expectations but, given the course title, you need to push more on Spark and leave the ML introduction to better courses like Andrew's one or a dedicated one.

Don't spare too much time with stuff like Course 2 and get some risks

By Francisco P J

Aug 2, 2017

Some parts of the course are quite interesting, in concrete, the introduction to the Knime tool (so useful and open source tool which I will try to take a deep look on it as the course only provide a slightly overview). Otherwise, i think that the content is not enough, i don´t feel that I have fully understand the core of Machine Learning and its difference with other BD applications.

By Sarwar A

Oct 13, 2020

I would like to give a three-star rating because of the following reasons:

1.Very Few Exercises

2.No challenging exercise

3.Only discussed Decision tree classifier

4.There are other important machine learning algorithms.

5.Overall I don't like the design of this course. It could have been degined to prepare learners for the industrial job

By Sebastián C L

Jul 12, 2020

Un curso introductorio a las técnicas de machine learning. Los ejercicios en Knime permiten entender el paso a paso de un proyecto de ML, mientras que los ejercicios en Python son prácticamente replicar el código ofrecido y no agrega valor a menos que conozcas muy bien este lenguaje de programación

By Beate S

Nov 16, 2017

I liked the theory parts, but had a to of problems with the hands on exercises: I spent a tremendous amount of time on installing/trying to install the necessary software. And not everything worked properly on my Mac Laptop.

By Javier P C

Feb 19, 2020

I like this course, but is very old and doesn't have methods for programming like python or other. Please check the content and upgrade the software, for me, it doesn't work Cloudera VM and is very sad. More Quality.

By Joren Z

Aug 28, 2017

A bird's-eye-overview introduction of the field. It teaches you some terms and it gives you ideas about which fields might be interesting for you if you want to really learn how to do machine learning with big data.

By Victor J O O

May 9, 2020

The course start excellent talking about categorical predictions but I would like see a similar explanation for regression or numeric predictions. However, the course offer an excellent quality.

By Santiago C F

Oct 5, 2020

The course tries to cover too many areas of Machine Learning, which ends up reducing the amount of time per topic, as well as the information you'll get to see.

By anilbkt

Jan 21, 2019

It would have been better if more case studies to work were given. I am surprised that there is no working case study given for regression analysis.

By Thorsten S

Jan 13, 2021

The course as such is not too bad ... BUT it's nearly impossible to do the hands-on exercises as Cloudera doesn't support virtual machines anymore.

By Mohan R S

May 30, 2020

The descriptive topics were The Handson exercise could be more elaborative. Many of the commands are just written but not explained.

By Alberto T

Jun 14, 2017

many basic of machine learning but not so specific to big data, only hands-on with pyspark is big-data related

By HILLEL D

Jun 21, 2020

Topics covered are good.

Outdated.

Hands-on needs to be updated. Exisitng set of 5th week contains error

By JAIDER M F T

May 12, 2020

El curso es introductorio no ahonda en los temas, me hubiese gustado que hubiese mostrado mas temas.

By Miguel T

Aug 17, 2018

I miss some technical information about machine learning techniques such as neural networks.

By Luis A

May 14, 2020

Very basic in terms of statistical techniques but liked the use of big data tools

By Akash R

Jun 6, 2020

this is more about ml classes, very less practical, only theoretical........

By Juan S H C

May 3, 2020

The Cloudera must to be checked. Too many errors in the Hands-On exercices