Retour à Mastering Data Analysis in Excel

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3,772 évaluations

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911 avis

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

30 oct. 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

13 oct. 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.

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par Bruno G

•17 janv. 2016

I would have liked the class to be less theoretical, with more frequent explanations linking concepts to practical applications in daily / business life, in order to keep interest and motivation high and facilitate understanding and memorisation. It sure would help to enter this course with a certain background of probability. Those memories were too ancient in my case :-(

par Andrew H

•19 mars 2020

Not recommended if you're a beginner. I don't understand a single bit of the math involved in this course, it is explained little if at all. Every time I start a video I have to stop and learn from elsewhere how to learn from this course. I'm sure it's great for people that know what is going on, but if you don't understand one thing at any point you're lost for good.

par Jade C

•7 mai 2017

I wish this course was more focused on building and analyzing data in excel. It feels like it's more focused on financial measurements and probability, it hasn't related to my line of work yet (marketing analysis). I wish the course also focused on advanced excel formulas outside of probability like advanced pivot tables, arrays, and macros.

par Anthony R

•29 févr. 2016

While the first week touched on Excel and the equations can be used in Excel and have efficacy in regards to analyzing data, it feels as if the course emphasizes more on utilizing math than utilizing Excel. And according to my understanding, that was what I thought I was signing up for. So, it felt like a bait-and-switch to me.

par Niyazi E D

•13 juin 2020

This Course has the wrong title, as many others mentioned prior to me. It was a lot about statistics and math, but the thing was that none of it was explained very well. It was unorganised and sometimes had crucial mistakes in it, which wasted a lot of my time. I give it two stars, because I learned a little Excel.

par Karolis M K

•1 nov. 2015

The course name is very misleading. While overall it is not a bad course, I believe a lot of people come here expecting very different material. Let's just put it this way: Mastering Data Analysis (mostly things to do with probability) with occasional use of Excel. Do not expect to learn anything new in excel.

par Ajai G G

•18 nov. 2016

Course did not meet any of the expectations. Neither Excel nor the analysis part. Should have focused on one of the aspects to make it more stronger. In my opinion "deviated" & stressed too much on statistics and model building (regression, logistic regression etc.) but did not do justice to that also!

par Rich

•2 mars 2016

Does not teach Excel very well while tryng to apply the basic usage instruction to not too difficult problems. The ability to interface with Excel after some knowledge of Python/R or other programming languages would be helpful in the Data Science programming that is increasingly being promoted.

par James B

•18 mars 2016

This class required far too much independent study. The instructor did not provide enough instruction or reading material to complete the quiz each week. There was too much focus on the conceptual data with very little emphasis on practical application of the material.

par Terry-Ann L

•5 mars 2016

This course is doable if you have prior knowledge of probability and statistics. This is not for beginners and should therefore by reclassified as intermediate and above. I am sorry I enrolled in this course. I have truly hit a brick wall and can go no further...

par Guillaume C

•17 nov. 2015

Way too many abstract concepts that are not relevant to the challenges that I encounter in my day-to-day role. I wish this course would actually show me how to solve PRACTICAL business problems.

The 2nd part of the course is not enjoyable at all. Sorry.

par Ivan K

•4 avr. 2020

There are dozens of formulas, but almost no examples and clear instructions of what to do step by step and explanation of how we can apply obtained knowledge in real world. One exception is the Markowitz Portfolio Optimization which is great.

par Loukas K

•4 sept. 2016

This course is only supported by a course of data analytics. It should clearly state that advanced statistics is a prerequisite knowledge. I expected to learn advanced excel techniques, not to be required to know statistic models to apply.

par Luke B

•1 oct. 2017

Poorly explained , you don't actually learn much excel . They just continuously provide spreadsheets for you without teaching you how to actually use excel for data analysis. Would not recommend for beginners wanting to learn excel.

par Gani

•6 févr. 2016

I feel that the course does cover adequate topic to improve our mastery of data analysis in Excel. The course is more focus on the statistic and probability theory without giving adequate explanation on how to work on Excel.

par Cheng-Kang C

•28 mars 2019

Extremely challenging to put so many concepts into one course.

I have to do my own studying and research outside of this course to catch up with.

However, it is a good start to follow what need to be learnt for data analysis.

par Lisa Y

•25 févr. 2016

In light of R or Python, doing statistical computing in excel is really time consuming and backward. The instruction might be OK, but I lost interest beginning of week 2 seeing how he build binary decision model in excel.

par Chester J

•2 sept. 2017

Lectures are messy, and assume more in-depth statistical knowledge than they have led-on in the course requirements. Quiz questions are also sometimes poorly explained and requires digging into the forums for corrections.

par Thierry M

•24 juin 2020

It is an okay refresher for Excel basics. But not a very good course for teaching you how to make a model using excel. The statistics and probability portions of the course were okay but definitely not taught very well.

par Gail C

•30 sept. 2020

Great class. However, there are some serious data mistakes in the projects. Please take the time to review and correct the errors throughout the course. It causes unnecessary confusion for the students.

par Luis d M O

•9 janv. 2016

Videos fine. Quizes impossible to understand unless you take previous courses and have time to go through forums and more extra staff. It takes a lot of time. Not suggested unless you have it.

par Phil M

•16 févr. 2016

I expected far more handy real life Excel examples, not to see a teacher speaking and writing stat formulas for hours.

The idea of this course is very good, it has some room for improvement.

par Candice S

•7 sept. 2017

This course is too focused on specific real world applications like confusion matrix and ROC curves that are very useful. I would rather spend more time learning actual features in Excel.

par Karina L

•7 mars 2017

Final project almost impossible to do with material taught. Also, each lecture comes with an additional spreadsheet that needs to be studied. Material taught doesn't match material tested.

par Christian H

•22 janv. 2016

Very confusing stuff, need better clarification in course description and the way the material is transmitted to the student need to be reconsidered

But very well made and interesting.

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