This course will expose you to the data analytics practices executed in the business world. We will explore such key areas as the analytical process, how data is created, stored, accessed, and how the organization works with data and creates the environment in which analytics can flourish.
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Habilidades que obtendrás
Universidad de Colorado en Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
- 5 stars73,99 %
- 4 stars21,34 %
- 3 stars3,16 %
- 2 stars0,54 %
- 1 star0,95 %
Principales reseñas sobre INTRODUCTION TO DATA ANALYTICS FOR BUSINESS
I really enjoyed the course. The subject was very well explained.and even the assignments were interesting.One can really take this course if you like playing around with data and having fun analysis.
I recommend this course for those who wants to learn about data analytics in business. The instructor delivers the material in an easy-to-understand way & the sample cases are on point as well.
It's a good course to get the feeling about Data and Analytics. For me it was quite redundant information but a good way to get familiar with the way Coursera and specific this course is working.
Overall the course is very good. As a beginner, it should be of a great start. But in the SQL week, more practise sessions should be intorduced specifically after every session.
Acerca de Programa especializado: Advanced Business Analytics
The Advanced Business Analytics Specialization brings together academic professionals and experienced practitioners to share real world data analytics skills you can use to grow your business, increase profits, and create maximum value for your shareholders. Learners gain practical skills in extracting and manipulating data using SQL code, executing statistical methods for descriptive, predictive, and prescriptive analysis, and effectively interpreting and presenting analytic results.
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