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

2015年10月30日

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

2020年10月13日

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.

篩選依據：

創建者 Luke R

•2017年4月6日

Good Course, but final project asks a lot for what this course is

創建者 steven u

•2015年11月22日

Good intro and fundamentals, but focuses far too much on finance.

創建者 Diogo H M d F T

•2016年7月7日

Superficial, esboça assuntos de estatística e mal fala do excel.

創建者 张之晗(ZhiHan Z

•2017年9月9日

So many terminologies, can you talk those principles concisely?

創建者 cherie

•2016年9月19日

Very hard to comprehend for 6 weeks. But could have been great.

創建者 Bernhard K

•2016年2月28日

Way too theoretical. This is Excel, not Information Theory....

創建者 Ernesto R

•2016年3月11日

Not enough practices for the unexperienced students.

創建者 Scott R

•2020年10月21日

Definitely way more statistics than I expected.

創建者 Neelam M

•2016年7月27日

inclination was more towards concept than excel

創建者 SARAH S A

•2017年7月18日

Tough Course.. Need Mathematical Background

創建者 Y. B

•2016年2月6日

good, but no material and lack of structure

創建者 Ricardo C

•2018年12月8日

Too much theory and no excel learings.

創建者 Reiko M

•2016年5月3日

Not so comfortable with using Excel.

創建者 Sundeep g

•2019年2月25日

It was great to have this course.

創建者 Hao C

•2016年2月9日

Not so relevant with real work.

創建者 Joseph M

•2016年5月2日

It was an interesting course.

創建者 Carlos S C

•2016年2月14日

Final project really hard

創建者 Vishal R

•2015年12月18日

Not much explanatory

創建者 Santiago B

•2020年5月27日

Very theoretical.

創建者 Syed A M K

•2015年12月12日

good course

創建者 Jorge D

•2015年10月17日

great!

創建者 Gabriel O C

•2016年7月5日

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!

創建者 Emanuele M

•2020年10月3日

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.

創建者 Noelle G

•2018年2月9日

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.

創建者 George T

•2017年3月8日

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.

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