Chevron Left
Retour à Foundations of strategic business analytics

Avis et commentaires pour l'étudiant pour Foundations of strategic business analytics par Ecole de commerce ESSEC

4.4
454 notes
102 avis

À propos du cours

Who is this course for? This course is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. For example, it may be suited to experienced statisticians, analysts, engineers who want to move more into a business role. You will find this course exciting and rewarding if you already have a background in statistics, can use R or another programming language and are familiar with databases and data analysis techniques such as regression, classification, and clustering. However, it contains a number of recitals and R Studio tutorials which will consolidate your competences, enable you to play more freely with data and explore new features and statistical functions in R. With this course, you’ll have a first overview on Strategic Business Analytics topics. We’ll discuss a wide variety of applications of Business Analytics. From Marketing to Supply Chain or Credit Scoring and HR Analytics, etc. We’ll cover many different data analytics techniques, each time explaining how to be relevant for your business. We’ll pay special attention to how you can produce convincing, actionable, and efficient insights. We'll also present you with different data analytics tools to be applied to different types of issues. By doing so, we’ll help you develop four sets of skills needed to leverage value from data: Analytics, IT, Business and Communication. By the end of this MOOC, you should be able to approach a business issue using Analytics by (1) qualifying the issue at hand in quantitative terms, (2) conducting relevant data analyses, and (3) presenting your conclusions and recommendations in a business-oriented, actionable and efficient way. Prerequisites : 1/ Be able to use R or to program 2/ To know the fundamentals of databases, data analysis (regression, classification, clustering) We give credit to Pauline Glikman, Albane Gaubert, Elias Abou Khalil-Lanvin (Students at ESSEC BUSINESS SCHOOL) for their contribution to this course design....

Meilleurs avis

PT

Oct 13, 2015

This course is excellent when it provides the citations very fit to theory. And I learned it in well organized structure of knowledge. Thank Prof. Glady and his team very much.

BB

Sep 28, 2017

Prof. Glady is an excellent lecturer. The course is very well produced, and the recitals were a great introduction to using code to solve business questions.

Filtrer par :

1 - 25 sur 98 Examens pour Foundations of strategic business analytics

par Sumit J

Dec 17, 2018

Very helpful course from career perspective.

par Purushottam Y

Jan 10, 2019

Good contents & course support, looking for more

par Ponciano R

Dec 20, 2018

Fantastic course. Focused on real life applications.

par Sébastien G

Jan 25, 2019

Very challenging for a novice in data science and R programming.

Learnt how to apply standard statistic models on datasets.

par ELINGUI P U

Jul 11, 2016

This gave me a great insight, and give me the will to learn and become an exeprt in R programming

par Alicia A M G

Sep 20, 2015

Awesome Course

par Ali N

Sep 26, 2016

Really worth it.

par Eldher H

Feb 08, 2016

Very interesting and insightful, it gave me tools and concepts which I can apply in my job.

par Shengyu C

Oct 23, 2015

Very relevant course

Teaches the interpretations of advanced analytic techniques - has a nice balance between the communications and the hard technical aspect. Would recommend it. However, for those who are not already familiar with the hard technical aspect, the course may be daunting.

par silvia j o p

Jan 26, 2016

Very complete and usefull

par Marcela G

May 10, 2016

Great!

par Keith P D C

Dec 03, 2015

Great course. The level of R needed to complete the course is very basic and a person having no prior knowledge in R could do it with some difficulty.

par tom p

Dec 03, 2015

Really good course - learned a lot. The approach was very friendly with guided exercises and code walk-throughs.

par Paul N

Jul 30, 2017

Some of the recitals are a little off and glaze over essential details. But, as a pragmatic and practical introduction to advanced techniques in R, I've not come across a better course. Very highly recommended.

par Mijail K

Jan 07, 2016

The better course I have ever realized on Coursera. Theorycally strong and truely applicable.

par Pedro M P

Oct 27, 2015

Amazing

par Nikos L

Dec 07, 2017

V

par Brad G

Sep 30, 2015

Fantastic examples of applied data analysis

par Man L

Jan 24, 2017

Very useful, practical anda easy to follow.

par Durga B P

Aug 15, 2016

Its OK

par Barnaby L

Apr 02, 2016

Great course which uses R to have you do classification, linear and logistic regression to address business topics.

par Edward H

Jan 21, 2016

I enjoyed this class, but the content feels amateurish. One major detracting factor is grading of the exams- a complete waste of time where there are multiple examples of contradictory slides to the quiz questions. The quizes often ask for information that is beyond the scope of the lectures and steadily becomes a process of just retaking exams until you get a 100%. I don't think the quizes reinforced the material in the lecture but actually took away from the class. This class was at it's best during the recitals, where I actually got to understand the great strategies used in the videos.

par Blaine B

Sep 28, 2017

Prof. Glady is an excellent lecturer. The course is very well produced, and the recitals were a great introduction to using code to solve business questions.

par Gordon S

Jun 28, 2016

This course does well to balance its focus on strategy and analytics. The analytics aren't overly in-depth, allowing for less technical individuals to reap benefits from the course. I highly recommend this course to consultants and business analysts.

par pham m t

Oct 13, 2015

This course is excellent when it provides the citations very fit to theory. And I learned it in well organized structure of knowledge. Thank Prof. Glady and his team very much.