Mastering Data Analysis in Excel

Final project is awesome but very practical and needs more clarity in videos and notes.

I found that the first part of the final project was the most difficult and time-consuming part of the course.

great course, the final project is really hard but I can really learn something.

The final project is a very good practice and it summarized most of the knowledge in this class.

Good for learning statistical analysis using real examples (bank credit card application) and hands on the data in the final project!

Nice Good Course, but final project asks a lot for what this course is Hello, I am Gabriel Wang from TAIWAN.

With some changes that course will fly high :) Final project almost impossible to do with material taught.

The lectures were mostly stuff I learned at school and really quite easy, but I just have no idea what the final project has got to do with the lectures.

Final project is almost a joke to try and decipher how to create from scratch based on the ones they provided in the quizzes.

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.

The lectures are quite abstract and the exam is a practical application of the concept.The instructions of the course also aren't very good as you need to do each part of the final project at the end of each week.I would strongly suggest to not take this course unless you have many spare hours.

Barely any practical application, does not prepare you for final project.

Well, it'll be good if you set the expectation that you're learning information theory and binary classification in this course, with Excel being the tool by which you use to learn those concepts.

Very good course Although more about Prob and Stat than learning to use Excel, concepts of binary classification and entropy are very interesting and are taught very deliberately and thoroughly.

I found Week 2: Binary Classification really confusing.

The professor explain you complex concepts like entropy or binary classification to continue with an excel worksheet.

The subject material is quite good, AOC and Binary Classifications were very interesting to learn about and have tons of applications, particularly in operation optimization problems/cases.

Great class to learn binary classification and prediction estimate.

I can learn how to build an effective binary classification model to support for my decision-making process.

Statistics, probability theory, binary classification are taught in very exciting and easy to perceive way.

It is incredible how some concepts clearly defined and put into practice turn into a a powerful tools for data analysis... like binary classification models, confusion matrix, bayes theorem.

Indeed a Mastering course for Data Analysis!

Really good course, I think the most value is at the end when you are able to apply the concept learned in the final assignment Great class, however I felt it was very heavy on statistics and math concepts versus how to use Excel for data analysis.

Very challenging course that is very insightful in the use of Excel for Data Analysis 很有趣的课程，作为基础性的知识很好地引导了学生的兴趣 im in week 4 , cant master data analysis in Excel Not much explanatory Great course!

great course got great knowledge about the models used for data analysis I like the course but sometimes the instructions are not clear enough.

really helped me understand the material for my job 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.

Thank you Challenging course, however very useful skills on leveraging Excel for data analysis.

The course is quite tough for me, but I enjoyed the topics discussed, primary between a binary model and a linear regression model.

If you've never heard of linear regression or Bayes Theorem don't bother with this course.

Fascinating materials (Markowitz optimisation, linear regression, information gain, binary classification...) with both theoretical and practical aspects!

Linear regression is not for sissies, in my opinion.

towards end of the course, specifically linear regression week, a lot of buzzwords are strung together.

Eg "This is the connection between linear regression and mutual information in a parametric model where we have gaussian distributions" I feel that each term in isolation I know what they mean, but when strung together, I am unclear how to process the meaning.

Professor Daniel Egger and his assistan MUST improve the lessons, including examples step by step specially for the multiple linear regression su I never knew excel had so much possibilities Very informative, and very challenging!

Would have liked to have had more explanation on linear regression, but overall everything was great.

The linear regression part, especially multivariate linear regression, need more explanations how to derive the matrix in Excel.

Indeed the way the problem is set out it appears that you can choose between predictive linear regression OR binary classification.

The core components of this course were binary classifications, linear regression, and the supporting mathematical and statistical theorems.

If you don't have good math and statistic background then you better learn them first...I personally learnt a lot from this course even though could not get the certificate.

I have learnt a lot about creating models with training data set and testing the strength of the model on test data sets.

First few things are fine then the course turns the other way Excellent course, I learnt a lot and really enjoyed it.

The course was challenging and I learnt a lot.

The Course is fine, explanations and videos are a bit hard to follow at times.The final assessment is in my opinion very bad, as it i appears to me quite unrelated to the course it self.

This course has a lot to do with math and statistics and I find it really hard to follow especially when it comes to the final project.

It was hard to follow along with the lessons, because it was mainly present in formulas.

In the end a lot of the concepts were not that difficult to figure out - don't overthink things as well!

Most videos are of Dr. Egger writing out algebraic equations and discussing them, the excel component of Mastering data in excel come via pre-made calculators as attachments that you for the most part need to figure out on your own.If you do not have a good comfort level with stats then you will require more time to spend on understanding the spreadsheet and it’s use.It would be fantastic if Dr Egger could go through the spreadsheets as a part of the video and show a couple examples, hopefully revisions down the road !

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.

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.

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 recommend having a significant knowledge of statistics before taking this course.

The attendants might already have a good foundation of econometric and probability statistics before taking this course.

Make sure you have studied calculus and probability before taking this course.

Beware.Also I would strongly recommend finishing the course work for week 3 AND 4 BEFORE taking the quiz on probability and distributions.

In my opinion, this course isn't nearly about Excel as much as it is about probability and statistical analysis.

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.

There are other, higher-quality Data Science MOOCs available.

Good The course enables me to get the knowledge about binary classification and predictive models I think with these skills I feel well-prepared to excel my skills in Data Science.

Overall, I believe they need to improve how the content is presented, and how it's applied in a real world context.

Don't know how to apply the statistics and excel formula in real world situation.

although the contents are tough but they are essential skills that vital to survive real world data analysis.

Use of spreadsheets in the course is poorly explained, examples are not relevant to the spreadsheet you're told to use ; and the material is covered way too quickly.

The tough part is in hectic learning of a vast array of statistical terms, often poorly explained – and alost never applied to practice (it is true that some of statistical metrics are "applied" in quizzed but it is unclear what's their purpose besides computing yet another number).

Does not have a strong emphasis on Excel skills and the statistics models provided seem to be randomly chosen and poorly explained.