Zurück zu Mastering Data Analysis in Excel

4.2

Sterne

3,522 Bewertungen

•

830 Bewertungen

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

Oct 31, 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

Oct 14, 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.

Filtern nach:

von Jody P

•Nov 08, 2016

Though at the start of the program indicates no prerequisite I would suggest that you be familiar with Algebra and Stats. 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 !

It was challenging but not impossible, and if you do not challenge yourself how much are you really learning?

Best of luck!

von Xu Z

•Nov 27, 2017

Professor Egger is pretty good at explaining concepts and make the class interesting. However, even to someone with solid statistical and math background, the class seems to have a steep learning curve. Concepts and projects can be discussed in more in-depth manner. Many classmates seem to be confused during middle of class. Be prepared to study up and research a lot using google search.

On the other side, I thought that it's an Basic Excel class before staring. Apparently I'm wrong. I picked up a lot of learning on data analytics side and how to use excel to accomplish the analytical goals. This class would be useful to anyone wants to get the exposure.

von Sarah L

•Aug 19, 2019

This course was much to focused on math proofs of statistical reasoning and left the actual instruction in Excel and how to use those formulas for mere supplemental material. The organization of the course left me in tears as I was struggling to understand the math and only THEN was I shown the application of that math to something useful. This is backwards. It needs to focus on the use of excel, not handwritten math formulas and proofs, and teach us the things we actually need to learn for the exam (how to compare 2 models, etc) instead of leaving us googling for the most pertinant information while the professor drones on about greek letters.

von Derek O

•Oct 25, 2017

While I found this course useful, it was originally advertised with the Data Analytics Specialization from Duke University, and it says that you need no previous knowledge to complete the specialization. I found this course VERY challenging and I think it is because of my limited experience in the fields of statistics and calculus. There were many times when vocabulary, formulas, calculations, etc. are mentioned quickly and I felt a little left behind. With some background in business statistics I think this class would be much more effective.

von Markus S

•Nov 20, 2015

Really interesting course and material and a very good instructor. This would be a 5 stars course if it wasn't for the final project. During lessons some concepts of statistics were taken as known (which is okay). However the final project required to utilize a combination of all new learned material on a whole different level of difficulty compared to the preceding quizzes. I did not expect that jump in difficulty and enjoyed the course a lot but the final project just was a struggle.

von Stefano J N

•Apr 29, 2016

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. 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.

von Kristin K

•Feb 27, 2018

The course covers some good topics, but it is not introductory due to the requirement that you have prior knowledge of statistics. I found the lectures got progressively more confusing with few examples of how to apply the knowledge. If you take the time to figure out what is actually being asked and how to do it in the spreadsheets provided you can learn something, but the amount of time wasted hunting for the correct approach to their spreadsheets can be quite frustrating.

von Dhananjay P

•Mar 15, 2016

The class has great concept but it needs a bit more structure and change to hit its full potential.

The Good:-The spreadsheets and exercises along with Quiz material. The project was also very informative.

The Bad:- The video need to better explain how Area Under Curve and how the Credit model make sense. It was not very intuitive and I struggled for over 2 weeks to put the Project together due to this gap.

But a worthwhile class with great potential. I am glad I took it.

von Darryl B

•Oct 22, 2020

The course is not updated and you have to depend on students solely to get through the material. There are several learning gaps. It would be better if they said that, these topics aren't covered but you need to read up on them. The lecturer style of delivery is not engaging so it is a challenge to get through the videos. The content and concept, that is the ability to determine a model using Excel is cool.

von Mohit M

•Jan 04, 2016

Course contents are rather deep which is good and makes it challenging. Explanations could be better and there should be more content on some topics for better understanding. Someone with background in statistics would find this course more useful than on who only has basic knowledge of statistics. Nevertheless, it inspired me to learn from other sources to fill the gaps in my understanding.

von Grant V

•Apr 05, 2017

Leve of difficulty was above my expectations. Moved too fast. Could have been more thorough in applying the content to examples similar to the quiz. Seemed to stick to the bare minimum of what would be required before moving to the quiz. Be transparent with future prospective students that this course absolutely requires knowledge of calculus, probability, and statistics.

von Thao V

•Nov 16, 2015

The course has some valuable information, however course materials and videos are not so helpful. If you already have some knowledge about statistics and excel, it will be a lot easier to follow the instructor's lectures, otherwise I don't feel how a beginner could really follow up on this course. Some topics are run through so quickly that they are confusing to students.

von Ambreen H

•Mar 23, 2016

This quickly became a statistics course, which although important was really difficult for me as I went in not expecting it.

However, Dr. Egger is incredible! I think he's a fantastic and well-versed instructor in the Data & Analytics realm and am eager to find ways I can use what I've learned into practice at work.

von Marta M

•Feb 02, 2016

I would like to have more example, it feels there is mostly theory. The quizzes were super easy, I dropped out at final project, I couldn't get through the first questions. The course (and especially the final project) requires a good basis in statistics beforehand.

The assistants are super helpful and patient.

von Christopher C

•Aug 15, 2016

The instructor should spend more time putting equations and concepts into concept, and tying them together. It often felt like values and questions were arbitrary. This is less about master data analysis in Excel, and more about gaining ground in a few key concepts, so the title is misleading as well.

von Allen O

•Jun 30, 2020

The quality of the content did not meet my expectations. There were typos, incorrect answers, and vague explanations. Courses like these, which are fully online and do not have any sort of support besides the forum, really need to make sure everything is robust in terms of content and quality.

von Sam H

•Aug 22, 2017

Difficult and too condensed for a beginners course. Although I appreciate that some of the worksheets were put together for us, I can't understand the underlying concept as well as if I were the one putting everything together. Logistically, it's not appropriate for a class this short.

von Nicholas J S

•Nov 29, 2019

I definitely learned a lot from this course, however, the teaching was very poor. The teacher is very hard to understand and much of my learnings I was forced to find elsewhere. Questions in the quizzes are not in coherence with the classes and one is often left very confused.

von Malcolm N

•Sep 20, 2016

nice syllabus overall with great exercises.

wish it would teach more commonly used excel skills in business e.g. pivot tables, index-match, vlookup etc.

lectures were a bit hard to follow (esp the mathy ones) - i'd suggest reworking the blackboard craft

von Marcus H

•Oct 15, 2020

Great course and an amazing professor; however, Week 4 and beyond should be redesigned. Linear regression is not that challenging of a topic, if taught well, and based on the discussion forums, too many people got lost at that point in the course.

von Pratyush A

•Aug 25, 2020

Too much mathematics. People who want to get deep into the working out analysis should do this course. If you want to learn basic analysis then its better you do some other course as this is heavy on theory and the quizzes are very tough.

von Ali H A

•Feb 14, 2016

This course did not live up to its potential.

The course should be retitled as an "Intro to Statistics" not learning functions and visualizations on excel.

I still have three stars because I at least picked up some useful concepts from it.

von Cynthia N

•Feb 07, 2016

Great class, however I felt it was very heavy on statistics and math concepts versus how to use Excel for data analysis. I would've liked to see some strategies on how to analyze large datasets, look for trends, and clean up bad data.

von Lieselot D

•Jul 17, 2018

The course was challenging and I learnt a lot. Some more practical exercises would have been helpful for me. Now everything came together in the peer graded assignment, where I missed some professional feedback to learn from.

von Nguyễn T B L

•Mar 11, 2016

The attendants might already have a good foundation of econometric and probability statistics before taking this course. Some definitions might be difficult to understand especially how it would be applied in real life.

- Sinn und Zweck im Leben finden
- Medizinische Forschung verstehen
- Japanisch für Anfänger
- Einführung in Cloud Computing
- Grundlagen der Achtsamkeit
- Grundlagen des Finanzwesens
- Maschinelles Lernen
- Maschinelles Lernen mittels Sas Viya
- Die Wissenschaft des Wohlbefindens
- Contact-Tracing im Kontext von COVID-19
- KI für alle
- Finanzmärkte
- Einführung in die Psychologie
- Erste Schritte mit AWS
- Internationales Marketing
- C++
- Predictive Analytics und Data-Mining
- UCSD: Learning How to Learn
- Michigan: Programming for Everybody
- JHU: R-Programmierung
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- KI für Medizin
- Guter Umgang mit Worten: Redaktionelles Schreiben
- Modellbildung von Infektionskrankheiten
- Die Aussprache des US-amerikanischen Englisch
- Software-Testautomatisierung
- Deep Learning
- Python für alle
- Data Science
- Geschäftsgründungen
- Excel-Kenntnisse für Beruf
- Data Science mit Python
- Finance for Everyone
- Kommunikationsfähigkeiten für Ingenieure
- Verkaufstraining
- Career Brand Management
- Wharton: Unternehmensanalytik
- Penn: Positive Psychology
- Washington: Maschinelles Lernen
- CalArts: Grafikdesign

- Zertifikate über berufliche Qualifikation
- MasterTrack-Zertifizierungen
- Google IT-Support
- IBM Datenverarbeitung
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI: Angewandtes Projektmanagement
- Zertifizierung in Instructional Design
- Zertifizierung in Bauwesen und -management
- Zertifizierung in Big Data
- Zertifizierung Maschinelles Lernen für Analytics
- Zertifizierung in Innovation Management & Entrepreneurship
- Zertifizierung in Nachhaltigkeit und Entwicklung
- Zertifizierung in Soziale Arbeit
- Zertifizierung KI und maschinelles Lernen
- Zertifizierung in Räumliche Datenanalyse und Visualisierung

- Abschlüsse in Informatik
- Business-Abschlüsse
- Abschlüsse im Gesundheitswesen
- Abschlüsse in Data Science
- Bachelorabschlüsse
- Bachelor of Computer Science
- MS Elektrotechnik
- Bachelor Completion Degree
- MS Management
- MS Informatik
- MPH
- Master-Abschluss in Buchhaltung
- MCIT
- MBA online
- Master of Applied Data Science
- Global MBA
- Master in Innovation & Entrepreneurship
- MCS Data Science
- Master in Informatik
- Master-Abschluss in Public Health