Retour à Mastering Data Analysis in Excel

étoiles

3,690 évaluations

•

886 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.

Filtrer par :

par Carmen R

•22 juil. 2016

This course was tough, but I dont mind a challenge. But what I found frustrating about this course was that first the quizzes were often inconsistent with the lecture material, the TA's were less helpful than my fellow classmates (without whom I would not have made it through the course) and the final was an IMMENSE challenge that took over my life for about 1 week - despite the calculation by the instructors that it would take 6-8 hours. I did give it a few stars because I honestly did learn things I did not know, and I understand the value of the application of what was taught for modern businesses. I have been informed that the course is being reviewed by the instructors for strengthening and I 100% agree with that direction.

par Belozerova I V

•25 janv. 2021

A lot of math and material that is not that easy to understand. If you thought that you would just be taught how to design data in Excel, then no, there is a lot of math waiting for you. Sometimes the material the teacher tells you does not match the examples on the Excel sheets and you need to figure it out by yourself.

I also didn't like that in weekly tests Excel sheets have to be loaded during the test. That is I lost enough time, because my Excel takes a very long time to open.

Especially the course is not very clear for those for whom English is not their native language. Some functions have different names in Russian, so it takes time to find the right function.

par Dan E

•27 juil. 2020

The course title is misleading. Various statistical methods are introduced in this course without much thought to ordering, then presented in pre-made Excel templates that are used for the course's final project. The analysis techniques are worth learning, but their connection is not clear, and the difficulty spike from the first week to the second and especially the final project is high. Additionally there were some mistakes in the course that lead to several hours of wasted time in preparing the final project. Prof. Eggers is obviously very knowledgable, so if you are willing to invest more time than the average, this course may be worth taking.

par Jason R

•20 juil. 2016

Beware this course, especially if you are new to this area (despite what the course/specialization says). 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.

I am extremely dissatisfied and wish I hadn't paid for this specialization. Beware.

par bisheng

•10 mars 2016

I am sorry to say this, but the tutorial could have been organzied in a much more serious way.

I do not know how much time the Professors have put on preparation. But it gives me a "sloppy" impression!!! The class carries the name of University of Duke and 70 euros are charged, so I think the learners would reasonably expect to see that the teacher puts lots of time to organize the course structure, in order to efficiently give as much as information to the learners within limited time!

For example, I believe nobody would not say that the Week 2 content on confusion matrix is very consistently explained. And this is just one example.

par Shulun C

•24 janv. 2016

The lecture videos are not super helpful and the instruction and support for final project is somewhat lacking. You need a relatively solid background coming into doing the project beforehand. Just study the course material is not enough for you to complete your final project, in fact you need peer help or to read more materials to fully understand and finish the project. The quizzes compared to what is asked in the project is too simple and thus not constructive enough in the overall learning. Overall I would recommend you to have a solid background before proceed with this course if you want to improve your learning experiences.

par Ryan K

•12 déc. 2015

The material is sort of interesting but there is not much hand-holding. I actually am an Excel beginner, and have merely an average grasp of mathematics. Before signing up, I read the prerequisites - there were none! It is advertised as a class for beginners, but I have found it beyond frustrating, and whats more I pre-paid for the specialization so this Excel class and the final project seem to be an utter waste of money without me going off to study Excel at length before trying the course again. Why not label it as an intermediate or higher class? I feel there should be a more obvious indication of the difficulty.

par Kartik K

•9 juin 2020

Only Suggested. If you've studied Maths/ Statistics in your undergrad, or if belong to a Commerce background. (That is the limit!)

And mind you, there are many glitches. Many.

There is no continuous flow; the video is not good; the audio is not good; the instructor seems way more casual and relaxed (even did a 15-20 second dance, can you believe it?!)

And sure the things taught and the things asked, are quite different from each other. But maybe if you've the 'needed' background, you might do it just as well.

Anyhow, if you do finish the course at last, it's all worth it.

I guess!?

par Чурсина К Е

•11 nov. 2020

This course has lower quality then others in specialization. Warning: it is concetrating on math not on Excel. This fact isn't bad by itself, but there is a big gap between video materials and quizes. There aren't enough practic examples which allow you to do graduated exercise confidently.

More than that there are a lot of cases of inaccuracy in automatic quizes and only forum discussins can hepl you understand that there is no your mistake.

Also sound is not perfect (in other courses it is much better) like it was recorded with home mic not professional.

par Alexander K B

•2 nov. 2020

The course material is very interesting and important for learning the mechanics of data analysis. However, the course organization and presentation is sub-par. Course assignments are often explained poorly, incorrectly, or not at all. Course videos are poorly organized and often difficult to follow for many reasons. After also completing another course by this instructor (Mr. Egger) I would steer clear of the courses that he teaches, if possible. When the learners in the discussion boards teach the material better than the instructor, there's a problem.

par Carlos A V J

•2 déc. 2015

It has a lot of problems, including: Not so many lectures about excel itself - most of the time you will be watching videos about statistic methods. The lectures are very superficial, even though the quizzes and projects demand a lot of knowledge and time. The course seems to have a staff of one man: the professor of the course rarely replies (even though he did at the beginning of the session) and all the work seems to be done by his assistant, who tries his best, but ends up not coping with all the questions asked at the discussion forums.

par Raimundo G

•12 janv. 2016

The content is really interesting and useful. However, the way in which the lessons are organised I'd say is confusing. The professor explain you complex concepts like entropy or binary classification to continue with an excel worksheet. 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. In consequence, the solution is always available.

In my opinion, it'd be better if a raw data set is given and you build the model step by step from the scratch.

par Manuela

•20 juin 2017

Though the course teaches important topics, I found the practical part of it rather lacking. The videos are mostly about the theory, using algebra and all that, but the exercises are on Excel spreadsheets that either you don't really need to do much (change a number here or there) or, when you do need to really work on it, there's no instruction provided other than the discussion forums and an one-page PDF. It was very disappointing, prepare yourself to spend a lot longer on this course, just trying to understand the spreadsheets.

par Corey D

•9 nov. 2018

The course is very poorly laid out. You are encouraged to work on your final project each week during each module but you don't learn important key elements to complete the final project until later in the course. I enjoyed what I learned in this class, however, stating there are no math prerequisites is misleading. If we were taught the concepts only in Excel, that would be one thing, but to hand solve these statistics problems by hand it really hurts the learn because the professor is speaking above most everyone's head.

par Øyvind M E

•13 août 2020

I think the learning objectives are good for the class but feel this course doesn't live up to the expectations. Personally disappointed in that we weren't taught how to build the Excel sheets and tools ourselves but rather were given ready made sheets that needs to be interpreted to be understood. I also believe that the quiz needs fixing as most if not all require checking the forum for "mentor hints" to fully understand what's being asked; in some cases, these don't help as the quiz has been changed/updated.

par Robin M

•10 avr. 2018

Actually a nice course but I feel completely lost with the last and final assignment. I looked through the forum, there are good hints but i still don't get it. It's frustrating that for the really hard stuff you don't have any explainatory videos from Prof. Egger so you can comprehend the material better.

I understand that one has to try to work out a solution with the methods given but a explanation of the difficult stuff afterwards would be quite helpful sometimes.

par Joseph C

•20 déc. 2020

Great information, but poorly executed or explained. There was inconsistencies in the quizzes and which resources to use. Information that was not updated over the lifespan of the course. When the course was first created there were errors found with the information provided. These adjustments were implemented but not updated in the actual course so the only recourse to find out what to do or which spreadsheet to use were only found in the discussion forums.

par Donna K

•20 sept. 2016

It is best to have a strong statistical background before taking this course. Lots of statistical calculations and procedures. If you don't have a strong background in statistics , there is a good chance you will get lost at some point in the course. There is no questions that the instructor of this course is an accomplished mathematician, I just found it hard to follow his lectures as he got deeper into various statistical aspects of the course.

par Donald L

•28 déc. 2015

Much work needs to be done on this course to make it friendly to learners. The quizzes and assignments do not align with what is taught in the lessons. Further, the content in the lessons does not even show or explain what is expected from the learning.

I spent the majority of my time exploring the discussions to discover what I was supposed to be doing and the rest of it on Google teaching myself the concepts that were not taught in the course.

par Valerie P

•5 févr. 2018

The professor jumps from subject to subject like if he assumes that people know the stuff he is teaching. Sometimes he goes on about something without telling you why he started talking about it, how it will be used, what is its relations with the whole course or at least that week's course. He even goes on to start the definition of a concept but then starts talking about an example and does not go back to the actual definition or use.

par Yoav S

•10 juil. 2017

First of all, it's important to point out that this course hasn't got a lot to do with Excel. It's more about statistics.

I am somewhat disappointed with this course. A lot of the assignments and tests were unclear, and it was hard to get clarifying information that will help you proceed. I was often left confused about some of the topics. Nevertheless, I learned some techniques that will probably be prove very valuable in the future.

par Philip g

•20 févr. 2016

I found this course too advanced for my level of familiarity with statistics. Its true that most basic stuff is covered to be fair, but the progression is very rapid.

As I work long hours and other commitments I didn't have enough time to dedicate to study beyond the time needed just for this course. If I had been able to study an extra 10 hours a week practicing using the formulas then I'm sure I would have got more out of it.

par Mark A

•8 mars 2018

The description of the course series does not adequately represent what is taught, more details up front about the material covered would have helped set expectations. The first course in the series focuses primarily on terminology, with little practical application. Almost all of the material was on finance & accounting.

In week 2 of this course, I realized this wasn't addressing what I expected and dropped out.

par Kevin R

•2 janv. 2017

All theory. Quizzes you were left with the task of answering questions based on models never seen or explained spent most time trying to make sense of them. Final project is almost a joke to try and decipher how to create from scratch based on the ones they provided in the quizzes. Its not a joke but it is very difficult when the actual excel and model making isnt part of the lectures.

par Justin M

•11 nov. 2015

So many equations presented without explaining why these things work or how they are derived. I'm having a hard time seeing the relevance. Also, I learned a lot of these statistics in college and the explanations provided in these lessons actually confused me about things I already know. Very disappointed in this course. Especially since part 1 of the specialization was so good.

- Recherche d'un but et d'un sens à la vie
- Comprendre la recherche médicale
- Le japonais pour les débutants
- Introduction au Cloud Computing
- Les bases de la pleine conscience
- Les fondamentaux de la finance
- Apprentissage automatique
- Apprentissage automatique à l'aide de SAS Viya
- La science du bien-être
- Recherche des contacts COVID-19
- L'IA pour tous
- Marchés financiers
- Introduction à la psychologie
- Initiation à AWS
- Marketing international
- C++
- Analyses prédictives & Exploration de données
- Apprendre à apprendre de l'UCSD
- La programmation pour tous de Michigan
- La programmation en R de JHU
- Formation Google CBRS CPI

- Traitement automatique du langage naturel (NLP)
- IA pour la médecine
- Doué avec les mots : écrire & éditer
- Modélisation des maladies infectieuses
- La prononciation de l'anglais américain
- Automatisation de test de logiciels
- Deep Learning
- Le Python pour tous
- Science des données
- Bases de la gestion d'entreprise
- Compétences Excel pour l'entreprise
- Sciences des données avec Python
- La finance pour tous
- Compétences en communication pour les ingénieurs
- Formation à la vente
- Gestion de marques de carrières
- Business Analytics de Wharton
- La psychologie positive de Penn
- Apprentissage automatique de Washington
- CalArts conception graphique

- Certificats Professionnels
- Certificats MasterTrack
- Google IT Support
- Science des données IBM
- Ingénierie des données Google Cloud
- IA appliqué à IBM
- Architecture Google Cloud
- Analyste de cybersécurité d'IBM
- Automatisation informatique Google avec Python
- Utilisation des mainframes IBM z/OS
- Gestion de projet appliquée de l'UCI
- Certificat stratégie de mise en forme
- Certificat Génie et gestion de la construction
- Certificat Big Data
- Certificat d'apprentissage automatique pour l'analytique
- Certificat en gestion d'innovation et entrepreneuriat
- Certificat en développement et durabilité
- Certificat en travail social
- Certificat d'IA et d'apprentissage automatique

- Diplômes en informatique
- Diplômes commerciaux
- Diplômes de santé publique
- Diplômes en science des données
- Licences
- Licence d'informatique
- MS en Génie électrique
- Licence terminée
- MS en gestion
- MS en informatique
- MPH
- Master de comptabilité
- MCIT
- MBA en ligne
- Master Science des données appliquée
- Global MBA
- Masters en innovation & entrepreneuriat
- MCS science de données
- Master en informatique
- Master en santé publique