Principles of Machine Learning

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23705 reviews

Course Description

This course is part of the Microsoft Professional Program Certificate in Data Science.

Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.

In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using R, Python, and Azure Machine Learning.

Reviews 8/10 stars
17 Reviews for Principles of Machine Learning

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Michael Taylor profile image
Michael Taylor profile image
8/10 starsDropped
  • 3 reviews
  • 1 completed
11 months, 2 weeks ago
This course assumes you have a fair amount of stats and calculus knowledge and it's helpful to have a little knowledge of R. It's also good to be technically persistent - I had several issues during setup that were frustrating. I was disappointed that the free version have very limited options in testing your knowledge - you could play around with the datasets provided but you were never challenged to do anything with them - often being asked to "answer questions" that you did not have access too. Somewhat related to this, I wanted one or two comprehension questions to accompany each video snippet - I've found generally this is the best way to ensure you are getting the main point (usually EdX courses are better about this). I listed myself as "dropped" only because I skipped over some of the material in the middle. Because I could complete the exercises, some of the middle sections on tuning was getting too much in the wee... This course assumes you have a fair amount of stats and calculus knowledge and it's helpful to have a little knowledge of R. It's also good to be technically persistent - I had several issues during setup that were frustrating. I was disappointed that the free version have very limited options in testing your knowledge - you could play around with the datasets provided but you were never challenged to do anything with them - often being asked to "answer questions" that you did not have access too. Somewhat related to this, I wanted one or two comprehension questions to accompany each video snippet - I've found generally this is the best way to ensure you are getting the main point (usually EdX courses are better about this). I listed myself as "dropped" only because I skipped over some of the material in the middle. Because I could complete the exercises, some of the middle sections on tuning was getting too much in the weeds for my tastes. I jumped to the end because I was interest in general how some of the other algorithms worked. The instructors were super knowledgeable and usually explained things in a way that could be understood and often had very practical comments about how this works in actual applications. While Dr. Rudin did a fairly good job explaining the math, it sometime became tedious - so I suppose that's what fast forward is for if you don't care about those kind of details.
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Gregory Taketa profile image
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Gregory Taketa

10/10 starsCompleted
3 years, 1 month ago
A tremendous improvement from the previous course (Data Science Essentials) because written materials have streamlined much of the learning. It's 1/2 theory and 1/2 Azure ML, so you can be selective about the content (I chose to follow most statistics videos for personal curiosity, skipped the Azure demos, and learned from the labs). Labs are excellent, as always. The labs prepared me to do well on the Final Exam. I have learned more about ML here than I have in formal university courses.
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Tim Shinabery profile image
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Tim Shinabery

3/10 starsCompleted
3 years, 1 month ago
Overall this course was disappointing. A huge amount of time was spent going over the statistics behind Machine Learning. That time would have been better spent going over the different methods actually used in the machine learning software and discussing how to properly select the right learning module for different problem types. The class was not a total waste as I learned something, but it could have been a much better course if they focused on actual machine learning and not on the statistics behind it. 20 minutes of statistics that go out the door with the selection of a single module in Azure ML, a waste of time and resources. I am disappointed with the course overall, it had potential but never achieved it. The instructors for this class were good, and did a decent job of presenting the materials.
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David R profile image
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David R

10/10 starsCompleted
3 years, 1 month ago
This course was without a doubt one of the most informative, engaging, and enjoyable courses I have EVER taken in my life. Period. Everything from the material presented, to the goofy mad scientist-like Dr. Elston and the wildly charming and dare I say very attractive Cynthia makes this course worth every second. The material is challenging. Very challenging. However, the instructors do a great job presenting the material, and the lab instructions are very simple to follow. At times, the labs can be drawn-out and complicated (especially lab 3 - break that lab up please...), but in the end I was able to take everything I learned and put together a model that predicted 23 out of 25 flights and their arrival times. This left an amazing impression on me and made everything thus far in my Data Science journey worth it. Take this course - you will not regret it.
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Keith Safford profile image
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Keith Safford

10/10 starsCompleted
3 years, 2 months ago
I had a lot of fun taking this course. It was difficult as there was a lot of theory involved, however, using Microsoft Azure ML took a lot of the difficulty out of performing the labs as a lot of the theory was taken care of by dropping the modules into the experiments. The two instructors also taught the Data Science Essentials class so that made things easier to comprehend as I was familiar with their style. I did email both the instructors a couple of times to clarify things on the labs and when I found discrepancies in code on Azure ML and running Python on my machine. Steve always responded quickly and gave me insight on my questions and helped. The only disappointing part was the final project as I completed and was able to finally get 21 out of 25 points for my model. Emailed Steve and Graeme about it and they said that was really good for a first stab at a predictive model. Did try something else for the incorrect one... I had a lot of fun taking this course. It was difficult as there was a lot of theory involved, however, using Microsoft Azure ML took a lot of the difficulty out of performing the labs as a lot of the theory was taken care of by dropping the modules into the experiments. The two instructors also taught the Data Science Essentials class so that made things easier to comprehend as I was familiar with their style. I did email both the instructors a couple of times to clarify things on the labs and when I found discrepancies in code on Azure ML and running Python on my machine. Steve always responded quickly and gave me insight on my questions and helped. The only disappointing part was the final project as I completed and was able to finally get 21 out of 25 points for my model. Emailed Steve and Graeme about it and they said that was really good for a first stab at a predictive model. Did try something else for the incorrect ones and was able to get 1 more point. My main disappointment is that if it is impossible to get 25/25 then there should be 25 tests and maybe 20 is the top number of points. Other than the final project, the course was outstanding and I learned a lot and plan to utilize what I learned soon.
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Student

10/10 starsCompleted
3 years, 2 months ago
I took this course as part of the MS Data Science curriculum. This was a valuable course and allowed me to get a good grasp of Azure ML. The math explanation was a great. You dont need much knowledge about python, you can just copy paste all the code used from the downloadpackage. I don't have any experience in this field, all the content was good to follow by a novice.
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student

1/10 starsDropped
3 years, 2 months ago
If you are an senior data scientist you may succeed in this course but you will not learn anything. and If you are a beginner you will drop and also you will not learn anything. this MOOC very difficult. I hope to see understandable courses and easy to learn like data science specialization on COURSERA or on UDACITY. The best describe for MPP in data science it is really difficult and for expert data scientists only and all courses talking about data science but it isn't learning students how to become data scientists. A complete waste of time and money.
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Student

8/10 starsCompleted
3 years, 6 months ago
This course was recommended to me by my manager, after completing a prototyping week where I chose to dabble in some basic ML techniques. This course has helped me appreciate the maths concepts, compare performance and explore ways of improving the models produced. Whats been nice, is that this was all done without getting bogged down in the code implementation too much, as even though Python is touched on briefly, the core functionality is handled by Azure ML. I feel this course is very accessible to anyone, as prior to this course, I had no experience in Python (.NET background), don't come from a mathematical background, but I did briefly learn about basic neural networks (perceptron) in University. I've completed the course with 94% and feel it's a brilliant stepping stone. I'd highly recommend it, even though it took me longer than the suggested hours (perhaps due to my lack of prior knowledge).
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Student

10/10 starsCompleted
3 years, 6 months ago
This was my 7th course in DS curriculum which I have somehow managed to complete with 83%. A very well carved out course but very inexperienced instructor in all my honesty. The lab videos are useless because the actual labs in the PDFs are very nice. So all in all even though I have passed and it was really difficult to pass it in the end(the final exam carries 50%) I doubt if I really have learned a lot from the course. Full 5 for content and provider but a 1 for the instructors.
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student

7/10 starsCompleted
3 years, 8 months ago
an ok intro to ML I think. this course alone won't give you any particular expertise in ML, however, you will need to supplement it via reading / practicing elsewhere.
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2/10 starsTaking Now
3 years, 9 months ago
I was very disappointed and was not able to make progress beyond Lab 1. I am now enrolling in the same class because this course is required for DS Certificate but I am not sure if it will be more successful. - I faced an error in ML environment while executing provided R code; - The instructor told me he could not replicate the error; - I believe I followed set up and lab instructions to the letter; - I consulted with ML person on my team, and she said it was something between R and ML integration and had nothing to do with R or ML on its own; - I spent hours and hours on this issue and I could have learnt a lot of materials during the hours that were wasted; - Eventually I was left on my own without any resolution.
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Youp Timmer profile image
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Youp Timmer

10/10 starsCompleted
3 years, 10 months ago
Even though this course has its issues (mistakes in code, questionable final exam, lab exercises not very challenging) I would certainly still recommend it. All of the content is explained for both R and Python, and towards the end also for SQL. Yes, the course features a lot of talking about Microsoft Azure - but I was happy to have gained knowledge about it. Other strong points of this course include: - Lots of content on different subjects within Data Science - Real life examples and lab exercises for practice, like predicting the price of a car based on certain features. - Step-by-step data science and machine learning process, like data mining, data cleansing, visualization, setting up a machine learning model and evaluating it, to using that model as a web service. If you have experience with Python or R, and want to learn how to use that knowledge to set up data science / machine learning models, this course is definitely wo... Even though this course has its issues (mistakes in code, questionable final exam, lab exercises not very challenging) I would certainly still recommend it. All of the content is explained for both R and Python, and towards the end also for SQL. Yes, the course features a lot of talking about Microsoft Azure - but I was happy to have gained knowledge about it. Other strong points of this course include: - Lots of content on different subjects within Data Science - Real life examples and lab exercises for practice, like predicting the price of a car based on certain features. - Step-by-step data science and machine learning process, like data mining, data cleansing, visualization, setting up a machine learning model and evaluating it, to using that model as a web service. If you have experience with Python or R, and want to learn how to use that knowledge to set up data science / machine learning models, this course is definitely worth taking a look at.
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Student

8/10 starsCompleted
3 years, 10 months ago
Like the course before it in the series, I thought this course gave some great worked examples of experiments in the lab portion, but didn't require students to do much of the design or coding. This gives the course a very reasonable pace but also means that there is a jump in difficulty later, when students need to design their own Azure ML experiment for the first time in the final project.
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Chris Barker profile image
Chris Barker profile image
10/10 starsCompleted
  • 8 reviews
  • 8 completed
3 years, 11 months ago
This course is part two of a two-part series of courses in the Microsoft Professional Degree in data science curriculum. I liked these courses and the way they were presented as Steve teaches much of the practical components in R (in my case) or Python and Cynthia provides an enthusiastic explanation of the statistical theory behind this. Of all the courses I am doing in the Microsoft data science curriculum these two are courses I might well go back over, just to reinforce the theory behind much of the statistics. I recommend paying close attention in this course and taking good notes as you will find these helpful in later parts of the curriculum especially the final project at the end. One aspect I liked about this course was the assessments which were a combination of comprehension questions and questions that required you to perform actions in R (or Python) to be able to answer--I found this quite satisfying as it reinforced tha... This course is part two of a two-part series of courses in the Microsoft Professional Degree in data science curriculum. I liked these courses and the way they were presented as Steve teaches much of the practical components in R (in my case) or Python and Cynthia provides an enthusiastic explanation of the statistical theory behind this. Of all the courses I am doing in the Microsoft data science curriculum these two are courses I might well go back over, just to reinforce the theory behind much of the statistics. I recommend paying close attention in this course and taking good notes as you will find these helpful in later parts of the curriculum especially the final project at the end. One aspect I liked about this course was the assessments which were a combination of comprehension questions and questions that required you to perform actions in R (or Python) to be able to answer--I found this quite satisfying as it reinforced that I was learning and absorbing the material.
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Student

8/10 starsTaking Now
3 years, 11 months ago
I would say this is a very hard course for me because I have very poor fundamental in math and programming. But, I still want to continue this course although it had been ended last Friday. Here just want to say thanks to Steve and Cynthia make this course! “If you can't fly then run, if you can't run then walk, if you can't walk then crawl, but whatever you do you have to keep moving forward.” I an slow in progress , but I do not want drop! A Chinese old student.
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Pankaj Bande profile image
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Pankaj Bande

10/10 starsCompleted
3 years, 11 months ago
This is a must course for all those who want to experience this field, very well planned videos and lab experience is just awesome.....i completed and learned and enjoyed every bit of it....so good to learn from Dr.Steve and Prof Cynthia....gr8 job, now waiting for my next one Applied Machine Learning....
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Robert Grutza profile image
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Robert Grutza

8/10 starsCompleted
4 years, 1 month ago
This is a great course for learning how to use Azure Machine Learning, which is a pretty amazing tool. It assumes the student has some background knowledge of machine learning and goes in depth on how to use Azure Machine Learning through detailed walkthroughs.
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