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.
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.
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Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in four to five months.
What background knowledge is necessary?
Ideally, your background would include some basics of data manipulation, statistics, and models for decision making. Learners must have working knowledge of Excel and some basic understanding of high-level programming instructions. This is not a computer science specialization but students will be learning some basic commands in SQL.
Do I need to take the courses in a specific order?
Although the four courses in the specialization can be taken separately, they are deeply integrated around their lessons. We recommend taking them in the order that they are offered.
Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
What will I be able to do upon completing the Specialization?
At the end of this specialization, you will be able to:
Apply data analytics to business problems. This involves the entire business analytics process, from data capturing, extraction, analysis, modeling, and presentation of findings.
Extract and manipulate data stored in large databases using SQL.
Identify and apply statistical models that are commonly used to implement descriptive analytics.
Apply predictive analytics tools to data sets and interpret results. In particular, you will be able to use Excel-based tools to construct models based on regression, simulation, and data mining.
Apply prescriptive analytics tools to data sets and interpret results. In particular, you will be able to use Excel-based tools to construct models pertaining to linear programming, integer programming, and simulation-optimization methods.