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# Avis et commentaires pour d'étudiants pour Mastering Data Analysis in Excel par Université Duke

4.2
étoiles
3,071 évaluations
694 avis

## À propos du cours

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....

## Meilleurs avis

##### JE

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.

##### NC

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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## 326 - 350 sur 676 Avis pour Mastering Data Analysis in Excel

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.

par Jiten P

Feb 10, 2020

Very detailed course introducing us to the foundations and concepts leading to analytics. However, I think the course could have been simplified, as it takes strong understanding of probability and related concepts as prerequisites.

par Evgeniy M

Nov 07, 2017

This course is about modeling but not Excel features.

I really enjoyed the course, but I had other expectations before starting working with this course.

I think, the title of the coure should be changed to minimize miscommunication.

par D. C

Jul 30, 2017

(Final Grade 91.4%). You will need to dedicate a time discuss course material with fellow learners, mentors, and instructors.

Update 07/29/2017 , I review the material , and they do a lot of corrections to the explanations ,

par Abbas K

Oct 19, 2018

This course although well taught was too difficult as it required understanding of higher level statistical concepts. That said I enjoyed the course and learned a lot for the instructor and the discussion groups. Thank you

par Joe G

Oct 19, 2017

Excellent starting point for data analysis, while prior knowledge of statistics and excel are not necessary, they do help with course comprehension. Would like to see future courses expand upon what was taught here.

par Joshua A

Jul 30, 2019

Great course and great professor, overall! The course was challenging at some points, especially when it came to the final project, but I really feel as though i learned some valuable skills from taking the course.

par Vitalija K

Feb 17, 2016

I really enjoyed the course. Professor was very good at explaining everything. And the team was very helpful. And this course is definitely for people who already has a good backround in exel and working with data.

par Wenqi Z

Jan 05, 2016

This is more than just an Excel course. It also covers a lot of statistics and the application of statistics in Excel (with pre-built template). I think more focus on how to build things in Excel will be useful.

par Irina

May 30, 2017

Very interesting course, but I think too much information for such short period of time. For me was difficult to understand und combine all given methods. More practical business cases would help here as well.

par Keith P D C

Dec 03, 2015

Most concepts are rather theoretical and it feels more like a probability and stats course. There is not much focus on excel implementation and life is made seemingly easy with all the templates provided.

par Mike B

Mar 18, 2016

Difficulty (at least for me) was non-linear. Weeks 1-2 were very basic with weeks 3-4 moving into parts of stats that I don't recall from my college course so it took some extra work to apply the models.

par Tam N

Apr 02, 2019

I like the course but sometimes the instructions are not clear enough. The learning materials are good. Yet I feel it takes so much time to finish the course because I feel not being instructed clearly.

par Shanta S

Dec 15, 2016

Tougher than the first in the specialization. You have to spend time on the material to succeed. In the end a lot of the concepts were not that difficult to figure out - don't overthink things as well!

par Matthew C C

Feb 28, 2016

Highly useful and practical course. it can be a bit challenging for Uni graduate from irrelevant field.

the First course and the visualisation course from this series of specialisation is okay .

par Nicholas A P

May 12, 2018

It was a great course and I learned a lot. However, I think the final project could have been more spaced out. In general, I felt like I needed more time at the end to review Excel Modeling.