The Analytics Edge

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10/10 stars
based on  154 reviews
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Course Details

Cost

FREE

Upcoming Schedule

  • On demand

Course Provider

edX online courses
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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.

Provider Subject Specialization
Sciences & Technology
Business & Management
22830 reviews

Course Description

In the last decade, the amount of data available to organizations has reached unprecedented levels. Data is transforming business, social interactions, and the future of our society. In this course, you will learn how to use data and analytics to give an edge to your career and your life. We will examine real world examples of how analytics have been used to significantly improve a business or industry. These examples include Moneyball, eHarmony, the Framingham Heart Study, Twitter, IBM Watson, and Netflix. Through these examples and many more, we will teach you the following analytics methods: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. We will be using the statistical software R to build models and work with data. The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge). It is a challenging class, but it will ena...

In the last decade, the amount of data available to organizations has reached unprecedented levels. Data is transforming business, social interactions, and the future of our society. In this course, you will learn how to use data and analytics to give an edge to your career and your life. We will examine real world examples of how analytics have been used to significantly improve a business or industry. These examples include Moneyball, eHarmony, the Framingham Heart Study, Twitter, IBM Watson, and Netflix. Through these examples and many more, we will teach you the following analytics methods: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. We will be using the statistical software R to build models and work with data. The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge). It is a challenging class, but it will enable you to apply analytics to real-world applications. 

The class will consist of lecture videos, which are broken into small pieces, usually between 4 and 8 minutes each. After each lecture piece, we will ask you a “quick question” to assess your understanding of the material. There will also be a recitation, in which one of the teaching assistants will go over the methods introduced with a new example and data set. Each week will have a homework assignment that involves working in R or LibreOffice with various data sets. (R is a free statistical and computing software environment we’ll use in the course. See the Software FAQ below for more info). In the middle of the class, we will run an analytics competition, and at the end of the class there will be a final exam, which will be similar to the homework assignments.

Reviews 10/10 stars
154 Reviews for The Analytics Edge

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Nick Thanasoulias profile image
Nick Thanasoulias profile image

Nick Thanasoulias

10/10 starsTaking Now
4 years, 9 months ago
One of the best courses I have taken regarding analytics. It covers many topics and goes through a variety of applications. I consider this course a must for anyone with an interest in analytics.
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Leonardo Noleto profile image
Leonardo Noleto profile image
10/10 starsTaking Now
  • 1 review
  • 0 completed
4 years, 9 months ago
good introduction to some ML methods (linear regressions, logistic regressions, trees) and clustering. The Kaggle competition provided by the instructors is well organized and help you to gain deep understanding of practical use cases.
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Nalin Pasricha profile image
Nalin Pasricha profile image

Nalin Pasricha

10/10 starsTaking Now
4 years, 9 months ago
I have taken four MOOCs on data science. "The Analytics Edge' was the best of all. Mainly, because it is based on real life case studies - so it shows how data science is actually applied - not just the theory behind it. The instructors are also very good, they provided clear and precise instruction which, I think, saved a lot of the students' time.
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alkamid profile image
alkamid profile image
8/10 starsCompleted
  • 1 review
  • 1 completed
4 years, 9 months ago
I really like the examples in the course - the material is taught using real-world situations like Moneyball. I wish the course was more platform-independent, but it IS in fact partly a course of R software - if you are using other packages, you will struggle to get the right answers. It is not a flaw though, R is an excellent package. The assignments are a bit too lengthy and repetitive, they could be made slightly more interesting, but I'm being picky here. The only thing that I feel needs improving is one instructor: Dimitris. The way he talks through videos is just halting and uninteresting - please let the girls speak, they do it very well! The best part of this course is by far the Kaggle competition. It is great because it forces us to change our mindset from closed questions from homework assignments to an open-ended problem where we are free to experiment using all the knowledge from the course. The interactions on the Kagg... I really like the examples in the course - the material is taught using real-world situations like Moneyball. I wish the course was more platform-independent, but it IS in fact partly a course of R software - if you are using other packages, you will struggle to get the right answers. It is not a flaw though, R is an excellent package. The assignments are a bit too lengthy and repetitive, they could be made slightly more interesting, but I'm being picky here. The only thing that I feel needs improving is one instructor: Dimitris. The way he talks through videos is just halting and uninteresting - please let the girls speak, they do it very well! The best part of this course is by far the Kaggle competition. It is great because it forces us to change our mindset from closed questions from homework assignments to an open-ended problem where we are free to experiment using all the knowledge from the course. The interactions on the Kaggle forums were great as well and many of us learned a lot from each other. The final exam was very well pitched and required using most of the techniques we learned during the course. Definitely a great course to take: well prepared, full of valuable content and challenging.
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Darius K profile image
Darius K profile image

Darius K

10/10 starsTaking Now
4 years, 11 months ago
This is fantastic course which is quite challenging, demanding quite some time (compared to other moocs) and at the same time it captures all your attention so that you cannot move away until you solve all the tasks. And then you have to wait impatiently for the next weeks material to come out...
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Student profile image
Student profile image

Student

10/10 starsTaking Now
4 years, 12 months ago
Eager to learn
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Student

10/10 starsCompleted
5 years ago
I wish there were more courses like this one. It has the exact approach I like to take for the classes I teach. It is 100% hands on, practical, applied, case oriented, etc. I love the way it used R (well, I love R!!) to make sense of real datasets. I completely recommend it.
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student

10/10 starsCompleted
5 years ago
Best course I have ever done in analytics...easily understandable and covers the practical aspects..also provides some amazing insights into real world case studies...It has triple folded my fascination for analytics..thanks all of you :)
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Greg Hamel profile image
Greg Hamel profile image
10/10 starsCompleted
  • 116 reviews
  • 107 completed
5 years, 9 months ago
MIT’s The Analytics Edge is a course focused on using statistical tools to gain insight about data and make predictions. The majority of the course teaches analytic methods using the R programming language, but the final 2 weeks deal with solving optimization problems using spreadsheet software (LibreOffice or MS Excel). The course runs 11 weeks and covers R basics, linear regression, logistic regression, decision trees, text analytics, clustering, visualizations and both linear and integer optimizations. The Analytics Edge is a meaty course. It has a lot of content each week and it’s not easy to breeze through things like it is with many other MOOCs. There are graded quizzes after each video lecture and each week of new material has 4 fairly lengthy case studies to complete. One week is devoted to an analytics competition while the final week is reserved for a 4 part final exam. Some students on the forums claimed they were spending... MIT’s The Analytics Edge is a course focused on using statistical tools to gain insight about data and make predictions. The majority of the course teaches analytic methods using the R programming language, but the final 2 weeks deal with solving optimization problems using spreadsheet software (LibreOffice or MS Excel). The course runs 11 weeks and covers R basics, linear regression, logistic regression, decision trees, text analytics, clustering, visualizations and both linear and integer optimizations. The Analytics Edge is a meaty course. It has a lot of content each week and it’s not easy to breeze through things like it is with many other MOOCs. There are graded quizzes after each video lecture and each week of new material has 4 fairly lengthy case studies to complete. One week is devoted to an analytics competition while the final week is reserved for a 4 part final exam. Some students on the forums claimed they were spending 10 to 15 hours a week on this course. Coming into the course with basic knowledge of statistics and R helps a lot. It should be noted, however, that this course is not too math intensive. It doesn't spend a lot of time talking about formulas or nitty- gritty mathematical details; it mostly teaches you how to apply statistical functions and methods and interpret the results. Although this course requires a serious time commitment, it is time well spent. The Analytics edge is an excellent course that teaches a bunch of practical statistical tools and actually gives you enough practice using them through the lengthy homework exercises to gain some confidence with them and remember how to use them. Too many courses info dump syntax and concepts, but don’t back them up with practical problems to let you use what you've learned. The homework problems for this course are very well crafted and look at a variety of interesting data sets from basketball stats to tweets about Apple. I can’t even imagine the amount of time that went into putting all the homework exercises together; kudos to the team at MIT for their hard work. If you’re interested in learning some practical analytic methods that don’t require a ton of math background to understand, this is the course for you.
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Tri Suseno profile image
Tri Suseno profile image
10/10 starsCompleted
  • 2 reviews
  • 2 completed
5 years, 9 months ago
I have taken and completed more than 30 Coursera and edX courses, and this course is hands down the BEST course out of them all. It is very practical, very well designed, and have many applications drilled into us so that we remember. The competition week using Kaggle is also soo memorable where you get to compete in a real problem in a worldwide platform. The only suggestion I have about the course: MORE please!! MORE content, MORE length, MORE applications / examples. This course is just simply Amazing I want to experience MORE. Simply the best!
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Esteban Afonso profile image
Esteban Afonso profile image
10/10 starsCompleted
  • 4 reviews
  • 4 completed
5 years, 10 months ago
Far exceeded my expectations. From the description I came in thinking that the focus of the course was primarily to describe, from a qualitative, high level perspective, how various individuals and organizations used data and analytics in a variety of settings to get an "edge." While it does do this, the greater focus (and value) is in that it gets your hands dirty applying the most essential of analytical techniques to gain insight from a number of datasets using R. The weekly structure was two lectures sequences demonstrating that week's analytical technique on two different datasets, a recitation applying these methods on a third set, and then problem sets, typically applying what you learned in the lectures on 4 different datasets. The workload seems high, but the lectures and problem sets are so clear, well organized and structured, you should be able to get through them relatively quickly. 7 weeks into the class you take the tr... Far exceeded my expectations. From the description I came in thinking that the focus of the course was primarily to describe, from a qualitative, high level perspective, how various individuals and organizations used data and analytics in a variety of settings to get an "edge." While it does do this, the greater focus (and value) is in that it gets your hands dirty applying the most essential of analytical techniques to gain insight from a number of datasets using R. The weekly structure was two lectures sequences demonstrating that week's analytical technique on two different datasets, a recitation applying these methods on a third set, and then problem sets, typically applying what you learned in the lectures on 4 different datasets. The workload seems high, but the lectures and problem sets are so clear, well organized and structured, you should be able to get through them relatively quickly. 7 weeks into the class you take the training wheels off by participating in a Kaggle competition (open only to the class) where you apply the tools you have learned to predict happiness based on demographic and survey data from an app. Still have a couple weeks left in the class to go, but have enjoyed it so much, did not feel the need to wait to review it. Have completed a number of MOOCs, and I put the Analytics Edge up there as one of my favorites, along with Andrew Ng's Machine Learning class and Rice's Python programming class. Gets my highest recommendation. PS Have completely fallen in love with R in the process...
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Bud Gibson profile image
Bud Gibson profile image
9/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 9 months ago
I took the course to freshen my R skills and get a fuller overview on recent analytics practice. The first 9 weeks of the 11 week course strongly fulfilled those goals. The course is extremely practical and focused on real pitfalls you will encounter in analysis. It covers a good breadth of techniques and develops a strong sense of how to proceed with analysis once the data is cleaned. If I had to critique the course, it had two main shortcomings: 1\. The real challenge of any analytics problem is usually in the initial structuring of the problem, and then getting the data to answer the questions raised. I would have liked to see more discussion here. You would probably need a different course to more fully address the issues. 2\. The last two weeks are focused on linear and integer optimization using spreadsheet models. Really not relevant for me. This felt like an add-on for completeness. I felt I had an adequate grasp of the issue... I took the course to freshen my R skills and get a fuller overview on recent analytics practice. The first 9 weeks of the 11 week course strongly fulfilled those goals. The course is extremely practical and focused on real pitfalls you will encounter in analysis. It covers a good breadth of techniques and develops a strong sense of how to proceed with analysis once the data is cleaned. If I had to critique the course, it had two main shortcomings: 1\. The real challenge of any analytics problem is usually in the initial structuring of the problem, and then getting the data to answer the questions raised. I would have liked to see more discussion here. You would probably need a different course to more fully address the issues. 2\. The last two weeks are focused on linear and integer optimization using spreadsheet models. Really not relevant for me. This felt like an add-on for completeness. I felt I had an adequate grasp of the issues, so I dropped the course. A better way to spend the final two weeks would have been to focus on writing functions and doing other programming tasks in R. Still, I think this is a great course. I just stuck with it for the parts I was interested in. It beat just drumming around mailing lists and reading obscure web posts to get caught back up on R. I think online, opportunistic learners are different from people taking a college course to get an overview of a field. This still has too much the flavor of a college course.
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student

10/10 starsCompleted
5 years, 9 months ago
This is the one freaking awesome course. I have taken more than 40 courses, successfully completing 10 of those. Just do it. Put the work in. It's worth it. It's a career changer. I love it.
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student

10/10 starsCompleted
5 years, 10 months ago
"The Analytics Edge" is the best edX course for me. Its a well planned course that require very limited background. Lectures and exercises are well prepared for proper understanding and solving real life questions. It really gave me an edge in computational biology. I'm no more afraid of big data. Thank you for this opportunity......
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Thirumal Venkat profile image
Thirumal Venkat profile image
10/10 starsCompleted
  • 2 reviews
  • 2 completed
5 years, 8 months ago
I was a newbie when it comes to Analytics. This course requires a lot of determination from your side to complete, and also is filled with quiz questions with very counter intuitive answers. This really set me off onto the Analytics path. I have completed other courses on Analytics, as other reviews say this is the best course on Analytics online. The lectures are succinct, then there's recitation as well to reinforce whatever you have learnt. If you are ready to work hard without giving up then please try this course when offered again!
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Dianne B profile image
Dianne B profile image
8/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 9 months ago
I completed the course despite of its high workload. Yey! Taking Analytics Edge, I now have a better understanding on how to tackle problems involving data, and how to apply analytics in different fields.
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student

10/10 starsCompleted
5 years, 9 months ago
Exceeded my expectations. The high workload has a reason to exist and I was not bored neither lost interest because of it. The competition was not only cool but also a good way to measure what we've learned. Highly recommend.
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Student

10/10 starsCompleted
5 years, 9 months ago
I have taken courses in data mining/machine learning both class room and online, but The Analytics Edge stands apart from the crowd. The review,home work and exam questions are very thought provoking and gives excellent learning experience. The kaggle competition takes the course to next level, not to mention the "real world problems" dealt with in each course sections. Each of the course sections gives exposure to real world problem which gives immense practical experience. These are few points that can be considered when offering course next time 1) Course notes for topics - This will help students to understand advanced areas like cross validation etc 2) Sample code 3) Reference material for topics 4)Extra optional problems
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student

10/10 starsCompleted
5 years, 9 months ago
This is one of the best courses I have taken online both at edX and Coursera. The course provides you with a solid understanding of different machine learning topics, and leaves you wanting more.
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kr strug profile image
kr strug profile image
10/10 starsCompleted
  • 9 reviews
  • 8 completed
4 years ago
A very good course introducing R as a statistic tool and spreadsheet solvers as an optimization platform. Gives perspective on how much insight you can get from numbers crunching. The course is focused on practical side, sometimes I felt that too little was said about R syntax. Maybe one more week of introduction would be usefull, but mayby it would get boring. Or maybe the R syntax is just little bit random and differs from library to library and that made me somewhat confused.
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student

10/10 starsCompleted
5 years, 8 months ago
This was the course that motivated me to keep learning online. Fantastic lectures, great topics, and truly useful work.
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T. A. profile image
T. A. profile image
10/10 starsCompleted
  • 4 reviews
  • 4 completed
5 years, 9 months ago
I consider this as the best MOOC I have taken, among some 15 or so completed. I had previously taken courses that used R and was eager for more practice. Your background will determine how difficult you think this is. Some other MOOCs had introduced even more challenging concepts (Stanford's excellent Introduction to Statistical Learning and Andrew Ng's Machine Learning course on Coursera). Neither of those offered nearly as many problems. If you think of quizzes and homework as puzzles, the volume of puzzles in this course was quite gratifying. Indeed, the sheer quantity of problems in this one made the experience of taking it qualitatively different from other MOOCs on similar topics. I really feel like this course helped me master several concepts and techniques I had previously seen. The required kaggle competition was a fun interlude, and might well have served as a gateway to a future addiction. The final two weeks entailed opt... I consider this as the best MOOC I have taken, among some 15 or so completed. I had previously taken courses that used R and was eager for more practice. Your background will determine how difficult you think this is. Some other MOOCs had introduced even more challenging concepts (Stanford's excellent Introduction to Statistical Learning and Andrew Ng's Machine Learning course on Coursera). Neither of those offered nearly as many problems. If you think of quizzes and homework as puzzles, the volume of puzzles in this course was quite gratifying. Indeed, the sheer quantity of problems in this one made the experience of taking it qualitatively different from other MOOCs on similar topics. I really feel like this course helped me master several concepts and techniques I had previously seen. The required kaggle competition was a fun interlude, and might well have served as a gateway to a future addiction. The final two weeks entailed optimizing using Excel Solver. I was already quite facile with Solver, but the course still managed to teach me a few things in the realm of integer optimization. The MITx team did a great job using all the features of the edX platform to their advantage. I especially appreciated having R scripts and Excel workbooks demonstrating ALL the lecture examples.
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Student

10/10 starsCompleted
5 years, 9 months ago
I have completed and audited 20+ moocs and this is at the top. This course represents the 2.0 state of the art version of moocs. The material and format are tailored for a mooc experience. Pedagogically it is very well structured. Just enough theory for understanding but not too much to bog you down. A lot of assignment work gives you experience. This is a large time commitment but time well spent.
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student

10/10 starsCompleted
5 years, 9 months ago
This course is a s good as it gets, very impressive lecture quality, practical, ambitious. So many thoughtful details. I liked the fast pace and that it required hard work to stay on top of the series which was very motivating and made me learn A LOT.
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Alessandro Malerba profile image
Alessandro Malerba profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 9 months ago
Absolutely amazing. Very difficoult and a very hard workload, but amazing ! Very practicle and very well designed. Bravo, bravissimo !
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Wang Cosmo profile image
Wang Cosmo profile image
8/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 9 months ago
i was surprised in the course, R is an opening project and it is very powerful,but lack of the learning materials.this course introduce something about Statistics Analysis,In particular,the statistics modeling,how to evaluation the model and use to prediction,it really is a very good course.
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Arnold Tanondong profile image
Arnold Tanondong profile image
10/10 starsCompleted
  • 8 reviews
  • 4 completed
5 years, 9 months ago
This is one of the best MOOCs I have enrolled, though I was not able to fully complete it due to time constraints and that I was also doing a harder course on Probability from the same institution. The materials are well organized. You don't even need an advanced background in Mathematics or Statistics or the software R to cope up with the lectures. This course will provide you a great reward such that you would be able to construct your own models to predict the quantities you may be interested in your daily life.
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Student

10/10 starsCompleted
5 years, 9 months ago
Amazing course! I learnt a great deal. The examples used in class and for assignments are very relevant and make me even more excited about the material. Overall, I really enjoyed the course.
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Dongguen Lee profile image
Dongguen Lee profile image
10/10 starsCompleted
  • 2 reviews
  • 2 completed
5 years, 8 months ago
Must great course in Ever!!!! I do already taken a lot of MOOC Course. But, this Course is most advance course, but most great course. I learn how can analysis Big data and makes better decisions. Actually I'm not a native english spoken, So I'm hestitate wirte reviews for this class, but, I definetly do wirte about this course. I'm now have confident to see the big data and analysis. This course has really good lecturers, and Community. So you can learan a lot of things about big data. It doesn't care who you are, Just take it.!!! ps. You have to put a lot of times(more than 10hours) on this course, have to understand and earn certificates. But It deserve it!!!!!
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Chandni Goenka profile image
Chandni Goenka profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
5 years, 9 months ago
I have done master's in economics where i had applied econometrics as a subject. This course was pretty different in terms of application related to real life problems. The case studies were quite unique and exhaustive. I WISH WE COULD LEARN SOME TIME SERIES ANALYSIS AS WELL USING R.
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