Chevron Left
Back to Machine Learning With Big Data

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

4.6
stars
2,441 ratings

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!

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.

Filter by:

426 - 450 of 494 Reviews for Machine Learning With Big Data

By Juan J R

Apr 20, 2020

Excellent Course

By Teja S C

Nov 23, 2017

great learning

By Verónica Y G Z

Sep 19, 2019

Esta Bien, :)

By Thomas Y

Dec 14, 2020

Good course.

By Anindya V G

Dec 3, 2020

Good course.

By 19E15A0509 M

Jul 10, 2020

goog cource

By siva R

Aug 23, 2019

Good one !!

By Carlos S d l C

Apr 2, 2019

Good course

By SAURAV P

Nov 7, 2016

insightful

By Isco22

May 20, 2018

Too Basic

By Rohit K S

Oct 13, 2020

Nice!

By Fabián S Á M

Sep 30, 2020

Good!

By Yash B

May 20, 2021

Good

By Hien B L

Jul 19, 2020

GOOD

By Bodempudi N

May 23, 2020

good

By SHREYAS J C

May 18, 2020

Nope

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