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Learner Reviews & Feedback for Mastering Data Analysis in Excel by Duke University

4.2
stars
3,908 ratings

About the Course

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....

Top reviews

TB

Nov 16, 2021

I like and appreciate courses provided through Coursera.This course is very interesting and valuable for those whose jobs do have relevance with data management .God bless Coursera and Duke University

JE

Oct 30, 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.

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501 - 525 of 934 Reviews for Mastering Data Analysis in Excel

By Irina T

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.

By Keith P D C

Dec 3, 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.

By Peilin T

Jun 21, 2020

The course is actually teaching you lots of stuff on statistics and probability but not on Excel. Also, the course needs better organization, many of the hints and resources are obsolete and need update.

By 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.

By Tam N

Apr 2, 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.

By 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!

By 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 .

By Yehor T

Oct 31, 2021

The final task in this course was quite a challenge to understand, I highly recommend reading forums for that. But overall - well-explained material with exceptional templates for future use.

By 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.

By Magnus K J

May 2, 2017

More respect after the course than before, as I thought this would be a pretty easy Excel course, but finishing it called lot of real work and statistical and modelling understanding.

By Alejandro G F

May 28, 2020

Learned a lot, no doubt. But the content could have been a little bit more helpfull regarding the final project, i found it really challenging in some aspects. Anyway, great course!

By Pengtao L

Apr 22, 2016

quite a lot techniques to learn. Just wish they could explain more about applications of those techniques, in more details, which however might be hard to get done in 5 weeks though.

By Klaus v K

Sep 17, 2017

An in depth deep dive into the mathematical concepts needed to be understood for data analysis tools and techniques. An all round good introduction into the field of data analytics.

By Luca s

Mar 14, 2018

I didn't rate 5 stars because I thinck there a are a few steps Prof. need really to enter more in details giving the solution to the diffent test but I really enjoied the course

By Pravesh S

May 8, 2020

Quite comprehensive on the usage of concepts taught in the course. However, bit of diversion seems to come in assignments and quizzes. Overall, very challenging and fulfilling.

By Ervandio I A

Nov 1, 2020

The concept is well explained, but the explanation about how to apply the concept to the case study is confusing, even though I know the basic knowledge about statistics.

By RENJITH M

Nov 10, 2019

Course is good for those who are looking to get skills in business analysis through excel. The final project does not have a proper reviewer or is not evaluated properly.

By Di Z

Jun 19, 2020

I really think the course should provide an example for the final project after submission because it was so confusing and none of my reviews has a good model. Thanks.

By Shalakha P

Mar 15, 2016

Very interactive and simple to learn course.

the video lectures are very clear to understand and worksheets are helpful to gain a better understanding of the topic.

By Ishir C

May 14, 2020

Loved the course. Concepts have been explained in detail with interesting examples. Please try and include a more detailed explanation of linear regression.

By Bonga L

Apr 19, 2016

So far i have found it useful. Most of the introduction elements are elementary but it gives you a chance to build up your knowledge and apply it as you go.

By Dionisio C

Jan 11, 2021

Very Good. At times too complicated questions for the explanations provided. Requires extra material outside the classroom not suggested and not vetted.

By Josephine

Nov 6, 2016

I feel this is way too hard for people who are not good at math, or haven't studies math for a long time. Took me longer time to figure all questions out.

By Rubén M F

Feb 15, 2016

I missed some more content in certain areas of the course (i.e. histograms). Apart from that, great course and great explanations by Daniel Egger!

By John S

Apr 10, 2017

Very useful knowledge in this course. Although, some of the quizzes require some small fixes, and there are minor mistakes in some lectures.