Вернуться к Mastering Data Analysis in Excel

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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....

TB

16 нояб. 2021 г.

I like and appreciate courses provided through Coursera.This course is very interesting and valuable for those whose jobs do have relevance with data management .God bless Coursera and Duke University

JE

30 окт. 2015 г.

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.

Фильтр по:

автор: Miranda F

•20 дек. 2020 г.

For a specialization labeled for beginners, I found this course to be very challenging compared to the other courses in the specialization. I expected that this class would cover pivot tables and how to find and interpret regression using Excel. This was not the course. The teacher explained concepts using upper division math, so I struggled to learn the concepts and did not have a teacher who could explain the concepts. The video lessons had very limited information. They assumed you knew the math already. The course would improve if it covered half the material and had exercises and worksheets that demonstrated how to do the equations.

автор: Benjamin C

•2 дек. 2015 г.

Warning: The lecture videos along will NOT be enough to prepare you for the final assignment! Be prepared to do your own research for the extra study materials. On the forum, many students said they had to drop out during the last week (probably without getting a refund!) because they were completely caught off guard by the huge knowledge gap between lectures and the final assignment. If you are determined to get the specialization certificate, you should definitely start the final assignment as early as possible. Don't wait until the last week or two!!

автор: aaron m

•23 июля 2019 г.

Completely disorganised. You will be tested on material BEFORE you take the lesson teaching it, making you question your ability. The outline they provide for the order you should take the materials is completely wrong. If you want to learn by a guy scribbling quickly and messily with little in depth explanation about the concepts he teaches, go ahead and take this. Otherwise, avoid at all costs. Also, you learn nothing about using excel to perform data analysis, just given templates with no explanation on how they work.

автор: Kamal G

•13 июля 2021 г.

The course was hard and not properly explained. They have only taught the concepts and mathematical formulas in videos instead of applying the concepts on Excel. They have provided reading material assuming students would understand on themselves how to apply the concepts on Excel. In the final course project, we were asked to prepare our model on own. However, throughout the course, it was not practiced. Now, how can a student prepare a model on themselves without practicing given that they only know about the theory.

автор: Fabio P

•24 апр. 2020 г.

There is no Excel here but a lot of theoretical and statistical topics that really make the lessons impossible to be understood if you don't have the appropriate background. At a certain stage, if you want to continue, you need to spend a lot of time to catch up trying to find on line what the trainer is talking about.

It is a pity because I used Coursera already and I was happy with their courses, but not in this case

автор: Robert N

•23 дек. 2015 г.

If I could give it less than 1 star, I would. It wasn't an Excel class, rather it was a targeted business statistics class with only disjointed lectures and no benefit of textbook to actually help you learn. Lots of errors in the lectures and tests, and little to no support from course staff. Stay away! You won't regret it.

автор: Meagan M

•11 июня 2021 г.

Finding a model in quiz 1 module 6 is too hard. I have spent hours trying various models, and have read every discussion thread and watched every video related to finding this model. All to no avail. I am unable to complete this course simply because of this one problem.

автор: Peter C

•27 апр. 2020 г.

I aced the first two weeks. It was recommended that I finish the first quiz of the final module. The information from the first two weeks would be fresh in my mind. I attempted the quiz, and encountered problems I was in no way prepared for.

автор: Junxi F

•22 июня 2021 г.

Lectures are lack of education, most of the questions are too hard and have not been explanied well. His homework are not associated with what he teaches, making the test parts extremely annoying and time comsuming.

автор: Bin W

•23 сент. 2020 г.

I am pretty sure that there are a lot of people who have problems with this course.

There should be more information and teaching for Test.

It's hard to utilize the things we learn from video for test...

автор: konstantin k

•29 мая 2021 г.

Useless. Poorly presented material and useless project. I would not recommend it at all. You are waisting your time if you enroll.

автор: Weston A

•22 февр. 2021 г.

lots of mistakes and errors, and videos are not enough to complete all the coursework

автор: Prasad H

•17 авг. 2016 г.

Though the Course name is Mastering Data Analysis in Excel. This course will take you beyond Excel mastering skills. Quite a Short Course compare to amount of Statistical and Probability concepts you learn. This course covers most of the concepts and models necessary for any Data Analyst & Data Science students and Professionals. This course is quite challenging and at times frustrating and time consuming but in the end you will feel you learnt something what you don't know. It will be worth your effort.If you don't know something what you don't know. Here is the course, it is an accelerated course. You many not master all of them, you will master some, I can assure any future students Professor will give all the information and concepts that you need to master. Even after completing the exam I keep repeating and going back to videos and notes which is really valuable.

автор: CHEN S H

•28 июля 2021 г.

The course title is misleading, at-least to me. I consider myself decent with Excel Data Manipulation, and hence would not have selected this course to learn. But stumbled upon this course by chance.

To my pleasant surprise, this course exposes you to model development for a credit-card company. You will have to work on sample data and come up with a simple statistical model to maximize the profit for credit-card underwriting.

These days, even though you can use machine learning software package like Scikit Learn to automate all these steps for model evaluation, as a practitioner it is important to know the mechanics behind it, and the best way to learn is through practice.

The assignment is difficult and it's difficult for a reason. Good things don't come easily.

автор: Rod S

•6 сент. 2016 г.

This course isn't for the faint hearted, you need a decent background in statistics, intermediate mathematics and good grounding in excel. All of these are covered well in the course but there's a lot to take in and I can imagine it being quite tough for those not so familiar. That said, the topics, examples and tools provided are exactly those required to build a good foundation in Business Analytics and I imagine, Data Science. Prof. Egger as always, delivers the course with great aplomb and shares his considerable knowledge in a wise but unassuming manner. Highly recommended.

автор: Ryan V

•29 дек. 2015 г.

I learnt a lot from this course. The first week seemed very straight forward and I was worried the course was a bit too rudimentary. From there it stepped up four or five gears and I had to work hard to reinforce the concepts and apply the concepts.

A really great course for any analyst or anyone seeking the true insight in data. The discussion board is a wealth of knowledge and a good read with tutors posting very plain english easier to understand answers to questions.

автор: Seshadri G

•28 июня 2017 г.

I got to learn life skills that are essential for a data analyst. The biggest addition to my knowledge via this course would have to be binary classification and entropy. Although I was familiar with the theory of probability and statistics prior to taking this course, everything was brought into perspective or context in this course. Grateful to Prof. Egger for his enoromous efforts in recording the videos and providing the spreadsheets for our practice and future use.

автор: Volney P

•25 июня 2017 г.

This Course is awesome!

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.

I am really enjoying this course... I highly recommended to everyone... thanks a lot professor Daniel Egger for sharing your knowledge with us, Coursera and Duke University for making this course available...

Hungry for more...

Volney Poulson

автор: Swetha J

•22 нояб. 2015 г.

Very good course. Loved Daniel's teaching. I have a request to make coming from healthcare/ lifesciences background and a starter to analytics it would be very very helpful if Daniel can include basic/ elementary videos on probability and statistics/ Bio-Statistics in this course to enable us to go deeper.

Else a separate course on BioStatistics and probability would be WOW. Looking forward for more courses from Daniel.

Thanks,

Swetha

автор: Sanal K

•20 апр. 2021 г.

I believe this is a great course for beginners in data science like me. I really loved the content of the course, presented with so many examples and prof Daniel Egger and his team has done a great job. I must admit that I did not understand many of the videos or concepts at first go, I had to do my share of background reading for every week. Once that is done, I guess you can takeaway so much more from these classes.

автор: Md. H I S

•28 мая 2017 г.

Excellent!!!

Its has so many things to learn; from understanding the data analysis process to building actual models. This course definitely laid the foundation of basic understanding and implementation of making decision thorough data analysis.

I would recommend this course to whoever is interested in learning data analysis or is involved in rational decision making through the data analysis.

автор: Lucia A I

•12 окт. 2020 г.

I liked the teaching methods and the content. You don't have to be an expert at Excel, but it requires certain experience in data analysis, algebra, and statistics, so you don't get lost when studying the content. I have an engineering's degree, so I'm not an expert in the topic, but I was interested and I feel satisfied with the knowledge I obtained and the challenges in the final project.

автор: Pavel K

•23 авг. 2018 г.

This course really improved my modelling and analysis skills. Apart from basic excel tools it gives an overview on very powerful statistic/predictive instruments. Statistics, probability theory, binary classification are taught in very exciting and easy to perceive way. Course project was not easy, but it took me to the next level of understanding. I cannot recommend this course more!

автор: Nicolas E

•10 июня 2016 г.

Very important course if you want to know more about data analysis. Fascinating materials (Markowitz optimisation, linear regression, information gain, binary classification...) with both theoretical and practical aspects! In spite the fact you won't learn much about VBA skills, this course will definitely give you a very good basis for addressing any data analysis problem with Excel.

автор: Karen H

•22 янв. 2016 г.

Very informative, and very challenging! The final project really challenges you to pull all of the concepts together in a real-world situation. That process helped solidify my understanding of the concepts.

Would have liked to have had more explanation on linear regression, but overall everything was great. I have a much more concrete understanding of the basics of data modeling.

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