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  • Provider Coursera
  • Subject Machine Learning
  • $ Cost Free Online Course (Audit)
  • Session Upcoming
  • Language English
  • Certificate Paid Certificate Available
  • Effort 4-9 hours a week
  • Start Date
  • Duration 4 weeks long

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Overview

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One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.

Taught by

Jeff Leek

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Reviews for Coursera's Practical Machine Learning
3.5 Based on 25 reviews

  • 5 stars 16%
  • 4 stars 40%
  • 3 stars 28%
  • 2 stars 12%
  • 1 star 4%

Did you take this course? Share your experience with other students.

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  • 1
Anonymous
1.0 3 years ago
Anonymous completed this course.
This course sucks. This is about machine learning. not about students learning. students don't learn anything with this course. apart from typing a one-liner code and pressing return.

This was supposed to be the last course of their data analytics specialization program. There is very little mathematical explanations, proofs, and the whole thing lacks a lot of rigour.

Worse, the data in the final data assignment has a lot of flaws, the provided testing data was actually (almost) a subset of the training data. Some people also figured out there were mistakes in the pro…
14 people found
this review helpful
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Juan D
3.0 4 years ago
Juan completed this course, spending 5 hours a week on it and found the course difficulty to be medium.
The name says everything, is just practical, none of the topics is treated in deep. And assumes that you have made almost all the other courses in the specialization.

There is a pronounced down in the quality of the weeks, the week 1 is good enough, and the week 4 just sucks. And the professors seems being hurried up in the videos.

However, can help as a very short introduction to a more in deep course.

7 people found
this review helpful
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L B
4.0 3 years ago
L completed this course, spending 7 hours a week on it and found the course difficulty to be hard.
This is good introduction to ML. The course demonstrate the practical application of ML, but due to short duration, it does not explain concepts in depth and it does glance over more complex parameters.

If you like to learn how to programme ML in R, have good experience with statistics and programming, and are happy with doing additional studies, I would recommend this course. For more in-depth knowledge I recommend Andrew Ng courese.
1 person found
this review helpful
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Brandt P
4.0 2 years ago
by Brandt completed this course, spending 3 hours a week on it and found the course difficulty to be easy.
This is the second-to-last course in the Data Science specialization from Johns Hopkins, and the final of three courses covering actual data analysis techniques (preceded by Statistical Inference and Regression Models).

This was one of the better courses in the series, and I thought it lived up to it's name. This was certainly a practical overview of machine learning techniques. There was very little discussion of the algorithms behind these techniques, certainly much less than even in Andrew Ng's Coursera course, which is itself supposedly fairly watered-down compared to many…
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Jason C
4.0 2 years ago
by Jason completed this course, spending 2 hours a week on it and found the course difficulty to be medium.
Of all the JHU Data Science specialization courses I've had, this was by far the most enjoyable. I really liked how the class was more in the style of 'here's some techniques, now do whatever you want on the project.' Prior courses are, and understandably so, more constrained in the assignments. It's not until here that the student really has the tools to be able to flex their analytical muscles, and it pays off.

Also, of the three instructors, I am most favorable to Jeff Leek, who teaches this class. He communicates much clearer than Roger Peng or Brian Caffo. I find I learn more from his content than the others.

Lastly, I will say that this class doesn't hold a torch to University of Washington's Machine Learning specialization. That's expected since this is one class and that's a whole series of classes. If you're hungry for more after this one, I highly recommend UWash's Machine Learning specialization.
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Anonymous
4.0 3 years ago
Anonymous completed this course.
I found this course very valuable. It isn't realistic to expect to become an expert in machine learning in the 4-5 days you might spend on studying the materials and, if you do, you'll be disappointed. However, it is a pretty good practical introductory course for those, like me, who start off knowing nothing about the subject.

If you're not too clear what machine learning is, what problems it can solve, and what the principles and procedures involved are, you'll find out in week 1. Weeks 2 & 3 are practical - you end up being able to use powerful tools like random forests for pr…
0 person found
this review helpful
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Prashant B
3.0 a week ago
Prashant is taking this course right now.
compare to some other course for deep learning i have taken this course really sucks.Does not give any understanding of deep network . Trainer seems to be quite dull in explaining concepts...
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Loki R
5.0 7 months ago
by Loki is taking this course right now, spending 20 hours a week on it and found the course difficulty to be easy.
This course is very useful one for me.Thanks for giving such a opportunity to me.Please try to teach us more advanced topics like this in future.
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Fabian H
2.0 3 years ago
Fabian completed this course.
1 person found
this review helpful
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Rafael P
4.0 3 years ago
Rafael completed this course.
0 person found
this review helpful
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Maresu R
2.0 3 years ago
Maresu dropped this course.
1 person found
this review helpful
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Jinwook J
4.0 2 years ago
by Jinwook completed this course.
1 person found
this review helpful
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Alex I
3.0 2 years ago
Alex audited this course.
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Sasidhar K
4.0 3 years ago
Sasidhar partially completed this course.
0 person found
this review helpful
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Phemelo L
5.0 3 years ago
by Phemelo is taking this course right now.
0 person found
this review helpful
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Mark B
3.0 2 years ago
by Mark completed this course.
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Colin K
2.0 3 years ago
by Colin completed this course.
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Radomir N
4.0 3 years ago
by Radomir completed this course.
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Hong X
5.0 2 years ago
by Hong completed this course.
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Stephane M
3.0 2 years ago
by Stephane completed this course.
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