Retour à Mastering Data Analysis in Excel

4.2

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3,213 évaluations

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734 avis

Important: The focus of this course is on math - specifically, data-analysis concepts and methods - not on Excel for its own sake. We use Excel to do our calculations, and all math formulas are given as Excel Spreadsheets, but we do not attempt to cover Excel Macros, Visual Basic, Pivot Tables, or other intermediate-to-advanced Excel functionality.
This course will prepare you to design and implement realistic predictive models based on data. In the Final Project (module 6) you will assume the role of a business data analyst for a bank, and develop two different predictive models to determine which applicants for credit cards should be accepted and which rejected. Your first model will focus on minimizing default risk, and your second on maximizing bank profits. The two models should demonstrate to you in a practical, hands-on way the idea that your choice of business metric drives your choice of an optimal model.
The second big idea this course seeks to demonstrate is that your data-analysis results cannot and should not aim to eliminate all uncertainty. Your role as a data-analyst is to reduce uncertainty for decision-makers by a financially valuable increment, while quantifying how much uncertainty remains. You will learn to calculate and apply to real-world examples the most important uncertainty measures used in business, including classification error rates, entropy of information, and confidence intervals for linear regression.
All the data you need is provided within the course, all assignments are designed to be done in MS Excel, and you will learn enough Excel to complete all assignments. The course will give you enough practice with Excel to become fluent in its most commonly used business functions, and you’ll be ready to learn any other Excel functionality you might need in the future (module 1).
The course does not cover Visual Basic or Pivot Tables and you will not need them to complete the assignments. All advanced concepts are demonstrated in individual Excel spreadsheet templates that you can use to answer relevant questions. You will emerge with substantial vocabulary and practical knowledge of how to apply business data analysis methods based on binary classification (module 2), information theory and entropy measures (module 3), and linear regression (module 4 and 5), all using no software tools more complex than Excel....

Oct 31, 2015

The course deserves a 5-star rating because: (1) content is relevant, (2) the professor is concise and possesses great teaching skills, and (3) the learning modules are applicable to daily problems.

Dec 20, 2016

Overall, the course material is good with many example. Need a general knowledge with mathematical and statistical from the beginning to pass the exam, because course slide is a little bit fast.

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par Jianxu S

•Oct 29, 2019

This course teaches the skills and techniques to build and analyze both predictive and classification models in EXCEL. The information theory treatment is unique and helpful to understanding the underlining business objectives and mathematical principles. Make sure you have studied calculus and probability before taking this course. I compare it to an entry level graduate course. Professor Egger is very good at teaching difficult concepts.

par Azar M

•Dec 02, 2015

Great course, great professor and great TA in community discussion. Can't give 5 stars as course introduction and content are not really matching. As per introduction anybody can take and learn this course, but indeed it is far from reality. If you don't have good math and statistic background then you better learn them first...

I personally learnt a lot from this course even though could not get the certificate. Thanks everyone.

par Jessica R

•May 13, 2017

Learned a lot, but instructions were often very unclear, especially in the final week. Luckily there were a lot of students who shared their approach of the final project on the discussion board, so it was easier to figure out what we were supposed to be doing. Without this input, I don't think I could have made it through this course. But overall, I felt really challenged and more ready to approach real world problems.

par Fil T

•Oct 26, 2017

The math in this course kicked my butt! It was good to be challenged by binary decision analysis. Tons of great spreadsheet resources here. In one of the quizzes, the incorrect data was given and it took me several weeks to find the correct datasheet but after I found it, everything was smooth. The videos all performed correctly.

The lectures did not exactly correlate to the quizzes, but it was enough.

par Vikas G

•Oct 03, 2019

That's a nice course. It just needs to improve the explanation a bit, which will help students not lose interest in the course and complete it on time without wasting much of time on unnecessary things.

However, on the bright side, wandering here and there on the discussion forum and figuring out the answers ourself was also one of the best part of this course.

par Piotr M M

•Oct 29, 2016

Difficult as hell.When You complete it You really start understanding this area but I think due to level of difficulty teaching staff should be a little more active.Big difference in difficulty in lessons(which are easy)and test(which are sometimes incredibly difficult).If You want to work in Big Data field You HAVE TO complete this course but...expect hell.

par Jan C

•Apr 22, 2020

Very useful course - during the course, I struggled a bit to be sure that I would be able to combine all the knowledge and put together into something meaningful in real practice, but the final assignments in week 6 were really great and through the step by step process of building the model I finally got the whole picture. And it is great! thank you!

par Will S

•Jan 13, 2016

Amazing volume of topics covered and in a manner that is not overly complicated in terms of testing methodology, but still requires you to do the work. There are still several bugs with the course, test answers and instruction documents on the site, but clearly the course is new so hopefully that will be resolved in coming iterations of the class.

par Jason C D A

•Jan 12, 2016

The course is more on analysis techniques as opposed to Excel shortcuts, tips and tricks. It certainly helps if you have a good background in algebra-level math; if you're looking for a course on how to be an Excel Power User, this might not be the best fit. Otherwise, what I learned here is useful for me. Thanks!

par Chua W T C

•Jun 29, 2016

The course is quite tough for me, but I enjoyed the topics discussed, primary between a binary model and a linear regression model. The addition of Excel into this course adds an application layer, which helps me to bring the concepts to the working world as well, and not just plain academic knowledge.

par Jose D P

•Nov 13, 2015

Excelente curso, pero a veces los vídeos o materiales se no son tan expresos en explicaciones y ejercicios para facilitar el entendimiento de lo estudiado. Por ejemplo la semana 2 de matriz de clasificación por su complejidad merecía mayor detalle en las explicaciones y ejercicios de práctica

par Adam S

•Sep 24, 2019

The course enables me to get the knowledge about binary classification and predictive models I think with these skills I feel well-prepared to excel my skills in Data Science. The tutor explained all mentioned issues clearly however the assignment and quizzes may be written clearly.

par Dali S

•Mar 08, 2018

Excellent course. I am a finance professional with limited statistics knowledge. Was able to follow the lectures. The reason for the 4 stars only is that the quizzes can be confusing with missing or misplaced information. Sometimes you have to search in the forums for hints.

par Colin M

•Mar 24, 2017

Good course, bit disjointed at times and some of the maths is rushed through, or not really relevant. Not sure I need proofs on why standardising figures results in easier to use data, maybe just show us how to do the analysis and apply it to more examples in real life.

par Ka L C

•Feb 17, 2020

I have learnt a lot about creating models with training data set and testing the strength of the model on test data sets. Every quiz is designed brilliantly. The only problem is that questions in the peer-reviewed assignment are not very clear and need some fix.

par YEVGENIY V K

•Feb 02, 2016

Lots of good information. However, this course could be structured a lit bit better. More examples and small practice exercises within the lectures would significantly improve the retention of material.

You should posses at least basic knowledge of statistics.

par Richard P

•Dec 27, 2015

Great information included. I feel like I know much more about modelling data than when I started. The quizzes can be in that without the hints on the discussion forum I don't know how I would have completed them just based on the information in the videos.

par Matt B

•Feb 17, 2016

I would have appreciated a bit more of a hands-on process in building the workbooks (with proper instruction of course) and more formal presentation of the formulas being used, but overall, I got a lot out of this course and enjoyed it along the way.

par K.S. V

•May 26, 2016

Although more about Prob and Stat than learning to use Excel, concepts of binary classification and entropy are very interesting and are taught very deliberately and thoroughly. More practise quizes and worked out examples would be even better.

par Victor W

•Nov 20, 2016

Course is very good! All examples are very clear and detailed. And a spreadsheet is provided to follow along during class. Only bad thing is that it was not so clear this course is heavily related to Math. Data Analysis = Math & Statistics. ;-)

par Jeff S

•Mar 09, 2016

Tough class but filled with useful and applicable ata analysis using the most popular and available program to do this work... Be prepared to get a little frustrated and watch the instructions more than once..... It's not Cousera fun fluff !!!

par Syed M R A

•Jan 31, 2018

Great clarification of concepts regarding "classification algorithm" and its application in various industries. Final project is awesome but very practical and needs more clarity in videos and notes. Overall, very challenging and informative.

par Andrew K

•Nov 18, 2019

Enjoyed the course overall. It's been a few weeks now, but I recall getting the sense that it needed a careful overhaul on quizzes. Some of the frustrations were mentioned in discussion groups that don't seem that well trafficked any more.

par Jose V

•Jan 30, 2017

The course is very challenging, but very interesting. I will probably suggest a bit more of staff support in the last week, specially the final project which is very challenging and demanding. A bit more of orientation will be really good.

par Mallikarjun B

•Sep 11, 2016

The explainations are a bit hard to follow if you are in a hurry, some times the course concepts just jump onto you. The techniques and content are really really great and very relavent, but the instructional value can be further ehnanced.

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