Back to Mastering Data Analysis in Excel

4.2

stars

3,378 ratings

•

787 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....

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.

Filter by:

By GBT

•Feb 24, 2019

This course has more holes than swiss cheese. The instructor makes major leaps without thoroughly explaining things. A lot of times when I started to do a problem set it felt like I had missed 2 or 3 lectures. But I had not, the instructor just leaves you to figure a lot out on your own. The videos are choppy often containing errors that sometimes have a note stating the accurate information. The excel sheets are posted at the end of the lecture as opposed to the beginning. But they have nothing to do with the lectures other than the calculus behind the formulas. So you have to go through cell by cell to figure out what the hell the instructor did and what calculus was being used. I appreciate how the instructor combined a lot of material here but unless you are fresh of calculus 3 or several statistics class then this is complexly crap course.

By Thomas S

•Feb 12, 2019

Horrible instruction. Little to no motivation is supplied for each topic. Moreover, the statistical concepts taught in this course are not preceded by preliminary concepts. For instance, I believe it is not until the course is almost over that the concept of a random variable is discussed. Do not waste your time with this course if your goal is to be more skilled in excel.

By Krishna K

•Feb 18, 2018

1. The scribbling on the videos is not legible. How do you expect students to learn when we can't read that scribble.

2. There is not enough detail within the instruction to complete the quizzes and final exam. I had to switch sessions multiple times in order to do additional research outside the course to complete the quizzes and exams.

3. This course needs a re-do. Please read what students are saying in the forum and on other MOOC review websites. The reviews for this class are NOT good.

Please make changes. I will NOT recommend anyone to take this class

By Will D

•May 21, 2020

By far the most upsetting educational experience I have ever had. This course has cemented my belief that good teaching ability is as rare among teachers as it is in the general population. No care or attention was placed in how to sequence the information, as it is presented almost as a stream-of-consciousness on the topics of statistics. There is absolutely NO substantive material in this course regarding data analysis within Excel. The only interaction with Excel you will have is playing with atrociously designed pre-made spreadsheets - only used to plug in numbers into cells. The course should be titled "A confusing and meandering review of statistical concepts", to at least avoid the embarrassment of claiming this course is on Excel - or that it will teach you anything. I strongly recommend that this portion of the course be dramatically improved or entirely removed if the instructor and Coursera have any value for their reputation or a clear conscience.

By Dennis N

•Sep 08, 2016

This course has nothing to do with Excel. It should be called "Statistic and binary modelling with little use in excel". If you except to learn about functions, pivot tabels, macros and the many other exciting features of excel, this is NOT the course for you.

By Mohammad A P

•Jun 24, 2019

The video just explains the basics but they dont take up detailed examples which are asked in the quizes and then it becomes very difficult to understand the concept

By Courtney B

•Sep 02, 2018

I learned a lot in this course, but it is definitely not what you would expect from the title! Like many others before me have mentioned, it's more of an advanced statistics course than an excel-based data analytics course. They provide spreadsheets that are already filled with formulas (you really don't get the opportunity to create them yourself, but they are pretty cool nonetheless), BUT they never use the spreadsheets in the lessons and DON'T properly explain how to use them; that said, you're required to understand how to use them for the exams!

I consider myself extremely capable with excel, and a very quick learner with a little bit of teaching and a handful of examples to test out, but when the lessons focused on math instead of how to fit a question to the spreadsheet, I felt pretty lost every time a quiz came around because we weren't taught how to use the spreadsheets to answer the questions (which would have been useful and applicable to my career, actually, unlike the math lessons). Most of the 6-8 hrs a week was not watching the lessons so much as messing around with the spreadsheets during quizzes and guessing where we needed to input data to populate the required results.

I'd honestly recommend this particular course only if it were redone in such a way that the lessons matched the exams better;Doing that would actually provide practical, applicable knowledge to the students.

By santiago p

•Jan 19, 2020

I write all this with a constructive approach to improve the course and not harm this great university and its brand.

The explanation and the videos do not correspond to the final project and or quices. Among other things, the creation of a mathematical model is requested and nowhere is it explained how to do it.

The videos and the contents are messy, the esthetics of the videos are not very careful and messy.

Isolated topics are explained without relating them to each other.

Because of the disorder, large thematic voids are left, which are unsuccessfully attempted to fill in superfluous and rapid explanations incorrectly inserted in the quices and final projects.

By Kaiquan M

•Jun 06, 2016

Misleading course name/title. Was expecting a course on using Excel. Forums were cluttered and not monitored often.

By Thanapich T

•Dec 28, 2018

Sheet is hard and too high complex for understand.

By Ryzhov V

•Feb 05, 2016

Not for beginners as promised. You need strong statistical skills to understand it.

By Amy H

•Mar 13, 2019

This is overall a great course for learning how to use Excel to analyse and manage data. However, the topics covered do not prepare you for the final project. I had to do a lot of trial and error, and research how to complete certain tasks, as the information given in the lessons is not substantial enough to complete the final project. On the plus side, this forced me to figure things out on my own and and taught me a lesson in perseverance. Coming from a humanities background, this course showed me the basics of using Excel and I now feel comfortable using Excel to analyse and manage large data sets.

By Ted Z

•Apr 28, 2020

This course has very little to do with practical data analysis in Excel and is really a view of how rudimentary modeling that no one would use in the real world can be done in Excel. The instructor throws calculations all over the place that are impossible to follow in illegible handwriting, never sets the background for the logic he's using, and then gives "calculators" for the quiz that can't solve the questions without significant reengineering.

There are much better options if you are are looking for a course that teaches you how to manipulate and transform data for analysis in Excel, and how to solve real world problems based on the power of spreadsheet formulas. If you're taking this course anyway to complete the Excel to MySQL: Analytic Techniques for Business Specialization, just know that you will be frustrated.

By Alexey K

•May 04, 2020

Course is not what it say it will be, 10 % out of all exel learning where teacher not mentioning that he is using Microsoft on apple and do not explain anything for windows users. 90 % of the course is statistics and high algebra. Name of the course should be (statistics and algebra as main focus) and exel just as support

By Ricardo A G R

•Jan 24, 2016

Unfortunately, the material and lectures of this course fell short of my expectations. Lectures don't follow a logical path and are all over the place, and some concepts are not expanded as required. Overall, I believe they need to improve how the content is presented, and how it's applied in a real world context.

By Christoph B

•Oct 31, 2019

Lots of calculation scribbled on black board, course material inconsistently named, structure difficult to asses, unclear which material to use for final test; reviewing peers: difficult to see, where question ends and answer starts

By Fons ' H

•Apr 18, 2016

No relevance to specialisation. Do not expect to get through this if you have not taken multiple statistics courses at university level or higher maths. Barely any practical application, does not prepare you for final project.

By KRUTI S

•May 08, 2019

I would not recommend this course to any one. The things they teach in videos and questions they ask on test are pretty different. First few things are fine then the course turns the other way

By Irene

•Nov 02, 2019

Try to explain all statistics knowledge to beginners but all are not in-depth enough which even more confusing!

By KOO

•Jun 26, 2016

Very poor lecture, I barely learn anything about excel from this course. The course title is quite mis-leading

By Daniel

•Nov 13, 2019

This course needs better explanations, there is a lack of details and you get lost easily.

By Paul J H L

•Feb 24, 2016

This is my first Coursera course and I wasn't sure what to expect. I was hoping for a good experience but preparing myself for mediocrity.

I finished the course at 2am on Monday morning and I've been really impressed, both with the Coursera "infrastructure" and with the quality of the teaching from Daniel Egger and his team. I live in South Africa where tertiary educational standards vary widely, and appear to be on the decline. More and more, we are going to need MOOCs like this from the best universities in the world.

More specifically, relating to this course, I found the video lectures well presented and the quizzes thoughtfully prepared. The Excel models really helped with grasping the concepts and practice.

A couple of suggestions:

a) The course FAQ makes light of the background knowledge necessary to cope with the course. It needs to be more honest about the need for mathematics and statistics. Linear regression is not for sissies, in my opinion.

b) Please tell us at the START of the course that we should attack the project week by week. This advice isn't (unless I missed something) given until you open the week 6 project. Ahem... it's too late by then! I spent a very frantic 4 nights last week crunching the project work, 4 quizzes and the assignment. I got to bed at 2.30am, and i'm not a night owl.

Overwhelmingly though, a really interesting course. I'm already starting the next one.

By Jason T

•Jun 12, 2017

This was more a statistics course than a

By Manuel E D L R G

•Jun 19, 2017

course is not related to the title

By Dieubon L

•Oct 12, 2017

The class could be better

- AI for Everyone
- Introduction to TensorFlow
- Neural Networks and Deep Learning
- Algorithms, Part 1
- Algorithms, Part 2
- Machine Learning
- Machine Learning with Python
- Machine Learning Using Sas Viya
- R Programming
- Intro to Programming with Matlab
- Data Analysis with Python
- AWS Fundamentals: Going Cloud Native
- Google Cloud Platform Fundamentals
- Site Reliability Engineering
- Speak English Professionally
- The Science of Well Being
- Learning How to Learn
- Financial Markets
- Hypothesis Testing in Public Health
- Foundations of Everyday Leadership

- Deep Learning
- Python for Everybody
- Data Science
- Applied Data Science with Python
- Business Foundations
- Architecting with Google Cloud Platform
- Data Engineering on Google Cloud Platform
- Excel to MySQL
- Advanced Machine Learning
- Mathematics for Machine Learning
- Self-Driving Cars
- Blockchain Revolution for the Enterprise
- Business Analytics
- Excel Skills for Business
- Digital Marketing
- Statistical Analysis with R for Public Health
- Fundamentals of Immunology
- Anatomy
- Managing Innovation and Design Thinking
- Foundations of Positive Psychology