Back to Mastering Data Analysis in Excel

4.2

stars

3,522 ratings

•

830 reviews

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....

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.

PW

Oct 14, 2020

The course was excellent. A little difficult and overwhelming at times but as long as you stayed the course the professors gave you every opportunity to succeed. Thank you for your time professor.

Filter by:

By Syed A M K

•Dec 12, 2015

good course

By Jorge D

•Oct 17, 2015

great!

By Gabriel O C

•Jul 05, 2016

PROS:

- Classification lecture is good;

-Weekly assignments are challenging enough

CONS

- No slides provided. Professor draws on an eletronic chalkboard (with a very bad handwriting) and you need to keep going back to videos when you are doing the homework. For me, this shows lack of professionalism and laziness

- Some excel sheets are provided. But they are very messy and badly formatted, matching the messy handwriting in the videos. AND, the instructions are for MAC! No instructions for PC are provided whatsoever. I never used MAC, so I had a very hard time!

- Very few examples real examples are provided;

- You learn math concepts, not Excel skills! Except for the LINEST function, which is very handy, BUT it's NOT TAUGHT in the videos. I had to google the function to learn it.

- They say to complete each piece of the final assingment after you finish the respective week related to that piece. But they only say that as you start week 6!

- The course doesn't provide sufficient material for the final assignment. You get stuck without knowing how to get to answers;

- Some answers to the final assignment are not correct, you check the answer sheet, and the results aren't present in the test!

OVERALL:

I'd never recommend this course to anyone. I only took it because I'm plannening to finish the specialization.

I've taken several Online Courses (5+ on Excel), and this is the worst and most frustating one by far!

By Emanuele M

•Oct 03, 2020

An interesting course, however, undermined by the number of topics addressed that for their complexity would have deserved a more systematic and less random treatment. The course is based on several pre-compiled excel files that should be a demonstration of the theoretical topics covered. This approach does not ensure the mastery of the theory by reducing the quizzes to the mere filing of cells with predetermined formulas.

I find the part on linear regression the most catastrophic. Having personally some basis of statistics, I have somehow managed to complete the course, but the treatment, especially with regard to the concept of entropy in information theory, should be completely revised. I don't understand why Professor Eggers doesn't start from basic concepts and then expand to more complex ones instead of the opposite. The final work, despite the formulation, is almost completely incomprehensible (check on the forums to believe), as unfortunately often happens here on Coursera is judged good-natured and the general level is very low, with a wide degree of plagiarism.

By Noelle G

•Feb 10, 2018

Understand that this is a course in Data Analysis that utilizes excel, not a course in excel. That being said, that's not my main reason for the lower rating. The math taught in this course is not geared well to people who struggle with math. Much of the learning time is devoted to understanding the math at a theoretical level. Much of the terminology is inadequately explained, and thee are too many instances of mathematical proofing over concrete, numerical examples. What numerical examples there are tend to be deliberately specific, simple and limited because the instructor wants you to take what you learned and apply it to the more complicated problems using your own understanding. Sadly this does not work when you don't understand the math with only a few simple examples and the theoretical reason as to why it works as a reference. Additionally the mentor for the course forums has very similar problems to the professor, relying on complicated mathematical terms and definitions that mean very little to someone who wasn't able to get it the first time.

By George T

•Mar 08, 2017

The course was a bit disappointing. We didn't cover enough advanced Excel functionalities, opting instead to focus on 2 statistical models (Binary Classification and Linear Regression). Having a BSc in Economics, the Linear Regression tutorials and quizzes seemed infantile, while the Binary Classification tutorials proved to be too vague, when we actually had to apply this knowledge on the final project. In retrospect, I regret not starting to work on the final week's material right from the start, which resulted in having to switch session multiple times in order to finish the course. Even if I had done so, though, it wouldn't have made up for the vague instructions in the quizzes and assignment of the final week that made feel at a loss, until I asked for help in the forums. All in all, this course need some serious re-working, in terms of how the material is presented and how the assignments are phrased.

By Monique P

•Aug 11, 2016

I did learn a few helpful tips for analyzing data with excel - particularly how to do a regression analysis in excel which is something I didn't know and is not intuitive. But for a course that is supposed to teach you how to analyze data in excel, there are actually very few lectures that actually show you how to do anything in excel. So much time is spent on how to calculate stuff by hand, without even mentioning how it translates to excel. Also the lectures have a lot of errors that were not corrected in a professional way. Just a random slide put in as an afterthought. The lectures got a bit disorganized towards the end, like the professor was in a rush and then forgot to relate everything to actual business analysis. The final project was especially difficult as not much was explained - I had to read the forums to figure out what I was actually supposed to do.

By Carmen R

•Jul 22, 2016

This course was tough, but I dont mind a challenge. But what I found frustrating about this course was that first the quizzes were often inconsistent with the lecture material, the TA's were less helpful than my fellow classmates (without whom I would not have made it through the course) and the final was an IMMENSE challenge that took over my life for about 1 week - despite the calculation by the instructors that it would take 6-8 hours. I did give it a few stars because I honestly did learn things I did not know, and I understand the value of the application of what was taught for modern businesses. I have been informed that the course is being reviewed by the instructors for strengthening and I 100% agree with that direction.

By Dan E

•Jul 27, 2020

The course title is misleading. Various statistical methods are introduced in this course without much thought to ordering, then presented in pre-made Excel templates that are used for the course's final project. The analysis techniques are worth learning, but their connection is not clear, and the difficulty spike from the first week to the second and especially the final project is high. Additionally there were some mistakes in the course that lead to several hours of wasted time in preparing the final project. Prof. Eggers is obviously very knowledgable, so if you are willing to invest more time than the average, this course may be worth taking.

By Jason R

•Jul 20, 2016

Beware this course, especially if you are new to this area (despite what the course/specialization says). There are very few examples to clarify and illustrate the different topics of the course, but what's worse is that the assignments are almost completely divorced from the instructional videos; the assignments and especially the final project are much more complicated than anything presented in the instructional videos, so there is no knowledge basis from which the student can operate to complete the assignments/projects satisfactorily or smoothly.

I am extremely dissatisfied and wish I hadn't paid for this specialization. Beware.

By bisheng

•Mar 10, 2016

I am sorry to say this, but the tutorial could have been organzied in a much more serious way.

I do not know how much time the Professors have put on preparation. But it gives me a "sloppy" impression!!! The class carries the name of University of Duke and 70 euros are charged, so I think the learners would reasonably expect to see that the teacher puts lots of time to organize the course structure, in order to efficiently give as much as information to the learners within limited time!

For example, I believe nobody would not say that the Week 2 content on confusion matrix is very consistently explained. And this is just one example.

By Shulun C

•Jan 24, 2016

The lecture videos are not super helpful and the instruction and support for final project is somewhat lacking. You need a relatively solid background coming into doing the project beforehand. Just study the course material is not enough for you to complete your final project, in fact you need peer help or to read more materials to fully understand and finish the project. The quizzes compared to what is asked in the project is too simple and thus not constructive enough in the overall learning. Overall I would recommend you to have a solid background before proceed with this course if you want to improve your learning experiences.

By Ryan K

•Dec 12, 2015

The material is sort of interesting but there is not much hand-holding. I actually am an Excel beginner, and have merely an average grasp of mathematics. Before signing up, I read the prerequisites - there were none! It is advertised as a class for beginners, but I have found it beyond frustrating, and whats more I pre-paid for the specialization so this Excel class and the final project seem to be an utter waste of money without me going off to study Excel at length before trying the course again. Why not label it as an intermediate or higher class? I feel there should be a more obvious indication of the difficulty.

By Kartik K

•Jun 09, 2020

Only Suggested. If you've studied Maths/ Statistics in your undergrad, or if belong to a Commerce background. (That is the limit!)

And mind you, there are many glitches. Many.

There is no continuous flow; the video is not good; the audio is not good; the instructor seems way more casual and relaxed (even did a 15-20 second dance, can you believe it?!)

And sure the things taught and the things asked, are quite different from each other. But maybe if you've the 'needed' background, you might do it just as well.

Anyhow, if you do finish the course at last, it's all worth it.

I guess!?

By Carlos A V J

•Dec 02, 2015

It has a lot of problems, including: Not so many lectures about excel itself - most of the time you will be watching videos about statistic methods. The lectures are very superficial, even though the quizzes and projects demand a lot of knowledge and time. The course seems to have a staff of one man: the professor of the course rarely replies (even though he did at the beginning of the session) and all the work seems to be done by his assistant, who tries his best, but ends up not coping with all the questions asked at the discussion forums.

By Raimundo G

•Jan 12, 2016

The content is really interesting and useful. However, the way in which the lessons are organised I'd say is confusing. The professor explain you complex concepts like entropy or binary classification to continue with an excel worksheet. It's here where the issue relays, the excel files are filled and instead of learning by doing you have to figure out how the prof made the file. In consequence, the solution is always available.

In my opinion, it'd be better if a raw data set is given and you build the model step by step from the scratch.

By Manuela

•Jun 20, 2017

Though the course teaches important topics, I found the practical part of it rather lacking. The videos are mostly about the theory, using algebra and all that, but the exercises are on Excel spreadsheets that either you don't really need to do much (change a number here or there) or, when you do need to really work on it, there's no instruction provided other than the discussion forums and an one-page PDF. It was very disappointing, prepare yourself to spend a lot longer on this course, just trying to understand the spreadsheets.

By Corey D

•Nov 09, 2018

The course is very poorly laid out. You are encouraged to work on your final project each week during each module but you don't learn important key elements to complete the final project until later in the course. I enjoyed what I learned in this class, however, stating there are no math prerequisites is misleading. If we were taught the concepts only in Excel, that would be one thing, but to hand solve these statistics problems by hand it really hurts the learn because the professor is speaking above most everyone's head.

By Øyvind M E

•Aug 13, 2020

I think the learning objectives are good for the class but feel this course doesn't live up to the expectations. Personally disappointed in that we weren't taught how to build the Excel sheets and tools ourselves but rather were given ready made sheets that needs to be interpreted to be understood. I also believe that the quiz needs fixing as most if not all require checking the forum for "mentor hints" to fully understand what's being asked; in some cases, these don't help as the quiz has been changed/updated.

By Robin M

•Apr 11, 2018

Actually a nice course but I feel completely lost with the last and final assignment. I looked through the forum, there are good hints but i still don't get it. It's frustrating that for the really hard stuff you don't have any explainatory videos from Prof. Egger so you can comprehend the material better.

I understand that one has to try to work out a solution with the methods given but a explanation of the difficult stuff afterwards would be quite helpful sometimes.

By Donna K

•Sep 20, 2016

It is best to have a strong statistical background before taking this course. Lots of statistical calculations and procedures. If you don't have a strong background in statistics , there is a good chance you will get lost at some point in the course. There is no questions that the instructor of this course is an accomplished mathematician, I just found it hard to follow his lectures as he got deeper into various statistical aspects of the course.

By Donald L

•Dec 28, 2015

Much work needs to be done on this course to make it friendly to learners. The quizzes and assignments do not align with what is taught in the lessons. Further, the content in the lessons does not even show or explain what is expected from the learning.

I spent the majority of my time exploring the discussions to discover what I was supposed to be doing and the rest of it on Google teaching myself the concepts that were not taught in the course.

By Valerie P

•Feb 05, 2018

The professor jumps from subject to subject like if he assumes that people know the stuff he is teaching. Sometimes he goes on about something without telling you why he started talking about it, how it will be used, what is its relations with the whole course or at least that week's course. He even goes on to start the definition of a concept but then starts talking about an example and does not go back to the actual definition or use.

By Yoav S

•Jul 10, 2017

First of all, it's important to point out that this course hasn't got a lot to do with Excel. It's more about statistics.

I am somewhat disappointed with this course. A lot of the assignments and tests were unclear, and it was hard to get clarifying information that will help you proceed. I was often left confused about some of the topics. Nevertheless, I learned some techniques that will probably be prove very valuable in the future.

By Philip g

•Feb 21, 2016

I found this course too advanced for my level of familiarity with statistics. Its true that most basic stuff is covered to be fair, but the progression is very rapid.

As I work long hours and other commitments I didn't have enough time to dedicate to study beyond the time needed just for this course. If I had been able to study an extra 10 hours a week practicing using the formulas then I'm sure I would have got more out of it.

- Finding Purpose & Meaning in Life
- Understanding Medical Research
- Japanese for Beginners
- Introduction to Cloud Computing
- Foundations of Mindfulness
- Fundamentals of Finance
- Machine Learning
- Machine Learning Using Sas Viya
- The Science of Well Being
- Covid-19 Contact Tracing
- AI for Everyone
- Financial Markets
- Introduction to Psychology
- Getting Started with AWS
- International Marketing
- C++
- Predictive Analytics & Data Mining
- UCSD Learning How to Learn
- Michigan Programming for Everybody
- JHU R Programming
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- AI for Medicine
- Good with Words: Writing & Editing
- Infections Disease Modeling
- The Pronounciation of American English
- Software Testing Automation
- Deep Learning
- Python for Everybody
- Data Science
- Business Foundations
- Excel Skills for Business
- Data Science with Python
- Finance for Everyone
- Communication Skills for Engineers
- Sales Training
- Career Brand Management
- Wharton Business Analytics
- Penn Positive Psychology
- Washington Machine Learning
- CalArts Graphic Design

- Professional Certificates
- MasterTrack Certificates
- Google IT Support
- IBM Data Science
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI Applied Project Management
- Instructional Design Certificate
- Construction Engineering and Management Certificate
- Big Data Certificate
- Machine Learning for Analytics Certificate
- Innovation Management & Entrepreneurship Certificate
- Sustainabaility and Development Certificate
- Social Work Certificate
- AI and Machine Learning Certificate
- Spatial Data Analysis and Visualization Certificate

- Computer Science Degrees
- Business Degrees
- Public Health Degrees
- Data Science Degrees
- Bachelor's Degrees
- Bachelor of Computer Science
- MS Electrical Engineering
- Bachelor Completion Degree
- MS Management
- MS Computer Science
- MPH
- Accounting Master's Degree
- MCIT
- MBA Online
- Master of Applied Data Science
- Global MBA
- Master's of Innovation & Entrepreneurship
- MCS Data Science
- Master's in Computer Science
- Master's in Public Health