Data Science Essentials

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7/10 stars
based on  21 reviews
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edX online courses
Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be tau...
Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.

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Sciences & Technology
Business & Management
23698 reviews

Course Description

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

Demand for data science talent is exploding. Develop your career as a data scientist, as you explore essential skills and principles with experts from Duke University and Microsoft.

In this data science course, you will learn key concepts in data acquisition, preparation, exploration, and visualization taught alongside practical application oriented examples such as how to build a cloud data science solution using Microsoft Azure Machine Learning platform, or with R, and Python on Azure stack.

Reviews 7/10 stars
21 Reviews for Data Science Essentials

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4/10 starsCompleted
3 years, 5 months ago
These videos are made very poor quality and it's very difficult to follow the instructor..Course content is not well organized based on topics
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student

9/10 starsCompleted
3 years ago
Great course, Cynthia is a fantastic lecturer, I am only sad I will never get to take one of her classes for real. Looking forwards to part 2.
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Brneden Knecht

10/10 starsCompleted
3 years ago
Overall this course proved to be extremely effective. I had limited exposure to data science prior to this course. I felt that this course completely prepared me for the Machine Learning that was to to come from the MPP program I am a part of. I would recommend this course to anyone who wants to get an intro to data science. The labs were easy to follow and proved to be very informative. I would say that you need to be self-motivated to take this course, but that is why you're on edx in the first place. Great course.
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9/10 starsCompleted
  • 0 reviews
  • 0 completed
3 years ago
Overall, i found this to be one of the easiest and most interesting courses on the track so far. Having been somewhat disheartened by the quality and presentation in the 'Essential Statistics for Data Analysis using Excel' course, i was pleasantly surprised to find this course revisiting some of the statistical material in a very clear and concise fashion. The material is very useful for beginners to Azure and Machine learning and has helped reinforce concepts learned through doing predictive work directly with programming languages. Some of the python code was quite difficult to follow. It is however, a very useful starting point for seeing how to automate generating graphical representations of data, by passing arguments to a function, and great for the exposure to matplotlib functionality. Presenters were great, engaging and concise.
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Naaj Ridh

8/10 starsCompleted
3 years ago
Overall, very solid course. This course covers a lot of needed "essentials" to be able to not only perform data manipulation and analysis (which are very important), but also exposes you to creating models and deploying them, which was fantastic. Pros: great refresher on statistics and probability topics, great coverage of topics, clear explanations. One very nice aspect was the way they would explain a topic and then almost immediately show a demo on how to practically implement it. I'm a very example based learner so that was very nice. One small con: assignments are too easy! They provide essentially step-by-step on how to do the assignment. Now, because I'm an example based learned, this was very useful. HOWEVER, you truly will never learn something unless you dive deep into a challenge and have to figure things out yourself. I have to struggle through the assignment, forced to remember topics, methods, concepts, forced to remem... Overall, very solid course. This course covers a lot of needed "essentials" to be able to not only perform data manipulation and analysis (which are very important), but also exposes you to creating models and deploying them, which was fantastic. Pros: great refresher on statistics and probability topics, great coverage of topics, clear explanations. One very nice aspect was the way they would explain a topic and then almost immediately show a demo on how to practically implement it. I'm a very example based learner so that was very nice. One small con: assignments are too easy! They provide essentially step-by-step on how to do the assignment. Now, because I'm an example based learned, this was very useful. HOWEVER, you truly will never learn something unless you dive deep into a challenge and have to figure things out yourself. I have to struggle through the assignment, forced to remember topics, methods, concepts, forced to remember techniques and code, otherwise I only have a superficial knowledge of it. I recommend that the assignment structure they have now, they should put as an ungraded "tutorial", where we are guided in answering the questions. For the real assignments, they should just give us a dataset and say "GO" with no aid. Other than that, course is excellent!
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Gregory Taketa

10/10 starsCompleted
3 years, 1 month ago
The topics and stories are great. This was the most time-consuming course in the data science track so far. A few tips for efficiency: -If you have taken the Statistics course already, only watch Cynthia's new topics on the subject (e.g. Correlation, Simpson's Paradox, Myths about P-Value). -If you can reverse engineer R or Python, you can skip most of Steve's demo videos and just learn from the labs a lot faster.
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8/10 starsTaking Now
3 years, 1 month ago
I think this course is difficult and content a lot of topics. But I think that is the way it need to be. I learn a lot from the course. I think instructor really do good jobs. Maybe some video is a bit too long it make students feel too tired to follow.
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Smith Adam profile image
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Smith Adam

1/10 starsTaking Now
3 years, 2 months ago
I think this MOOC for experts and post-doctoral students exclusively! I do not advise anyone to waste money here. You will not learn anything. Only (long, boring and complex) videos .
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Gabriel MV profile image
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Gabriel MV

8/10 starsCompleted
3 years, 3 months ago
As others have commented, the course is pretty broad, which is to be expected as this is an introduction course. I felt like the Labs were somewhat too easy as it was mostly copy-paste centric. The "Final Test" was actually very good which requires you to google and find external resources which, truth be told, is exactly what one will have to do in the future. You were able to use Azure ML, Python or R for part 1/2 of the final test. All and all, I would recommend doing the course, especially the final test which is a much more realistic approach to data science
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Miguel Meza

10/10 starsCompleted
3 years, 3 months ago
This course gave me a great overview of Data Science and Azure ML. The labs do a great job of walking through the material covered within the videos.
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Matt McMichael

4/10 starsCompleted
3 years, 5 months ago
I took this as a part of the Microsoft Professional Program Certificate in Data Science. Overall, the course is broad and worthwhile. In terms of statistics and data science, there is quite a bit of rehash that been taught over and over, yet Cynthia summarizes concepts really well and is an entertaining speaker. The coding aspects are literally copy and paste and while it was helpful to go through these step by step, especially with Azure, the coding education was sorely lacking. Since that isn't the focus of this course, it was very frustrating with the final exam that 2/3 of it was contingent on getting the coding correct. Since I couldn't get the code to work, I literally could not answer most of the final 2/3 of the exam. Again, since writing perfect code isn't the focus of this course, being able to get such a large percentage of final exam answers shouldn't be dependent on it. Also, if you don't get the first 1/3 of the e... I took this as a part of the Microsoft Professional Program Certificate in Data Science. Overall, the course is broad and worthwhile. In terms of statistics and data science, there is quite a bit of rehash that been taught over and over, yet Cynthia summarizes concepts really well and is an entertaining speaker. The coding aspects are literally copy and paste and while it was helpful to go through these step by step, especially with Azure, the coding education was sorely lacking. Since that isn't the focus of this course, it was very frustrating with the final exam that 2/3 of it was contingent on getting the coding correct. Since I couldn't get the code to work, I literally could not answer most of the final 2/3 of the exam. Again, since writing perfect code isn't the focus of this course, being able to get such a large percentage of final exam answers shouldn't be dependent on it. Also, if you don't get the first 1/3 of the exam correct, you are simply not going to get the rest of the final exam correct because it's one continuous problem/question. I would highly recommend auditing this course first so that you don't waste money just because of the final. I barely passed above the required 70%.
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8/10 starsCompleted
3 years, 7 months ago
I agree with Gabriele Reccia. Steve's level of details and slow talking makes the course boring. I always listen to him at 2x and jump multiple times.
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Gabriele Reccia

2/10 starsTaking Now
3 years, 7 months ago
Well, let's say that it's a really a boring course... - Instructors reads slides (thanks to God you have possibility to increase the speed of video, you really need for Steve Elston). - Labs are "copy and past" types.... brain is not necessary... If you are taking the "Microsoft Professional Program Certificate in Data Science" (MPPCDS) the previous course of R is not enough if you really wish to understand more. You need to study more alone, but it's not necessary to pass the course (copy and past will help you...) A good thing is the refresh of statistics of Cynthia Rudin, really valuable stuff. Nothing to say about the "promotion" of AML, I understand it, Microsoft is the provider of the course. Bad news: to take the MPPCDS you need to follow also Principles of Machine Learning course.... I really hope it will be less boring and with more brain teaser labs. In the end what to say: a bit disappointed of this course.
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Dean Hu

9/10 starsCompleted
3 years, 9 months ago
This paper is quite good which worse more than the existing 3.5/5. It's easy to follow and students could leave with a brief understanding of R, Python, Azure ML. But this course is only a into course and students will need to have worked with Python or R before they could do well. It will be great if the constructors could make the assesment harder and leave students some space to think for themselves and solve innovative problems. To sum up, this is a good quality paper, which should worse at least 4.5/5.
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Student

10/10 starsTaking Now
3 years, 9 months ago
I just finished the 2nd module and this course is a breathe of fresh air after drowning in the DS101X course. I have much more clarity with the the same basic concepts after a few minutes with Cynthia than hours in that course. As for Steve's quirky instruction style--more please, he keeps my attention (especially vis-a-vis "inaudible" and robotic instructors). The people who've offered bad reviews saying this is the "worst" or whatever, are obviously judging from an insufficient sample (i.e. haven't yet taken DS101X). But that's no slight on this course or the instructors. I feel like I'm finally getting "signal vs. noise" take on data science that's long been missing from a field whose barrier to entry has been guarded as if it were turf to be protected. Again, and more generally, this course if a breath of fresh air.
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A Student

7/10 starsCompleted
3 years, 9 months ago
The course is great for a complete beginner (like myself). I really appreciated the very detailed directions in labs--it was useful to learn how Azure works. The lectures were interesting, especially the ones taught by Crystal. It is possible to complete this course without understanding much, so you get out what you put in.
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Amir Charania

10/10 starsCompleted
3 years, 9 months ago
I thought the course was fantastic. The content covered was exceptionally well done. It had the basics of Statistics, Visualization and Machine Learning. The ability to play the videos at different speeds (0.5x to 1.25x, 1.5x, 2.0x) was invaluable. Overall, I would highly recommend it for anyone looking to get into Data Science
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student

8/10 starsCompleted
3 years, 10 months ago
For context, this course is part of a series: students learn some stats and how to program in R and Python before starting. The examples included in the course illustrate well what the platform is capable of doing. There is no question that the reader will be able to follow along with the labs. However, given the students' background from previous courses, I thought students could have been asked to do more thinking/coding in the labs instead of having the tasks dictated by the lab walkthrough. If this course (and the one after it) were moved toward the end of the data science professional degree program curriculum, that expectation would be even more reasonable.
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J Kim profile image
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2/10 starsDropped
  • 2 reviews
  • 1 completed
3 years, 11 months ago
Surprisingly bad experience. I feel that this course is made to advertise how good microsoft Azure is, and how easy Azure is to be used for machine learning. This course is definitely not for someone who wants to know what Data science is and what are the essentials of data science. Very disappointed, I dropped the course after 2 weeks when they started talking about Azure again and again, I noticed that something is not going right.
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John S profile image
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John S

2/10 starsTaking Now
4 years ago
Possible to provide more granularity on what the course is about in the introduction please? I am sure the course has more to offer but cannot gleam what that might be from such a brief intro. Disclaimer: the review is on the introduction not the course :)
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2/10 starsCompleted
  • 1 review
  • 1 completed
3 years, 10 months ago
Very disappointing course overall - by far the worst I've done actually. I'm sure the instructors are experts in their fields but I don't think they are able to teach. It seems like Steve just reads through slides/examples and is not able to say anything off-script without immediately getting muddled and confused and just trailing off in a mumble. It's a very distracting and frustrating experience to sit through hours of this (and he also teaches the follow-up course..). As for the labs, ironically, they could have been completed by a not-too-intelligent machine - it is a pure copy & paste exercise, where you learn very little. Expected more from Microsoft.
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