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Foundations in Business Analytics Certificate by the Numbers
12
Credits
5
Courses
2
Programming Languages
0
On-Campus Commitments
A Foundation for Business Analytics Success
Our Online MS in Business Analytics program is designed around four content pillars that we have identified as essential to success in the field—business acumen, math modeling, computing technologies and communicating with impact. The five business analytics courses that make up this certificate provide the foundations to these pillars, skills in each area upon which deeper expertise can be built.
Both the “Probability and Statistics” and “Linear Algebra for Business Analytics” courses provide essential background knowledge for the complex mathematical modeling that analytics roles demand. The certificate’s two programming courses—in R and Python—build your knowledge in the two most essential languages to contemporary analytics computing technologies. Finally, the program’s culminating course, “Competing Through Business Analytics,” ties these skills together with business acumen and communicational fluency, preparing you to apply business analytics tools in any organization.
And when you complete your coursework for this certificate program, it could be just the beginning of your analytics education. The five courses of the business analytics certificate program comprise the prerequisites and first required course of the Online MSBA program. Students who complete the Foundations in Business Analytics Certificate program in good standing are invited to apply to the Online Master of Science in Business Analytics (MSBA) program with no additional application requirements, and all credits from the certificate may be applied toward completion of the MSBA.
Learn In-Demand Business Analytics Tools
R and Python are two of the top five data science skills in highest demand, according to TechRepublic. 2
Online Foundations in Business Analytics Courses Overview
BUAD 502A Probability and Statistics I (3 credits)
In the area of probability, this course covers the concepts of discrete and continuous probability distributions as well as conditional probability. It also covers basic statistics, which can be thought of as a set of tools for interpreting data. These include descriptive statistics, which permit us to describe basic characteristics of data, including the computation of means, standard deviations and ranges of a data set. This course also covers inferential statistics, which are methods for uncovering deeper insights from the data, such as hypothesis testing. Finally, the course considers data visualization as an integral part of data analysis.
BUAD 502B R Programming (1 credit)
This course provides a set of programming skills using the R programming language, which is widely used in business analytics for statistical computations.
BUAD 502C Python Programming (1 credit)
This course provides a foundation of Python programming skills for business analytics including knowledge of Python data types, facilitating repeated execution through the application of loops, using conditional statements, programming the input and output of data, the use of Python packages, and the construction of functions.
BUAD 502D Linear Algebra for Business Analytics (3 credits)
This course provides a set of linear algebra tools for performing business analytics including vector-matrix multiplication, Gaussian elimination, computing determinants, computing matrix rank, computing matrix column and row spaces, performing eigenanalysis, and performing principal components analysis.
BUAD 5112 Competing Through Business Analytics (4 credits)
This course will include a survey of the state-of-the-art in business analytics, examining companies that have used business analytics for competitive advantage and how they have done so. This course will teach business acumen and how the field of analytics fits within the context of business. Topics will include business metrics as used for performance measurement and incentives, communicating with impact, visualization, and the functions of a company—how they interact, what data they have, and their development and deployment of algorithms. The course will also include a survey of opportunities for problem solving using business analytics in operations, supply chain, human resources, finance and marketing, as well as an introduction to the tools that are covered in the remainder of this program.
Foundations in Business Analytics Certificate at a Glance
- Complete in just over one semester
- 100% online
- No residency or on-campus requirement
- Multiple opportunities to start per year
- Study with our faculty of industry experts
- Completion in good standing can fulfill admissions requirements for the Online MSBA program
- All credits can be applied to Online MSBA
Application Requirements for the Online Foundations in Business Analytics Certificate
The Online Foundations in Business Analytics Certificate is designed to be an opportunity for anyone interested in pursuing an analytics career, at any professional level, to move into this dynamic field. To promote this level of accessibility, the application requirements for the program are as follows:
- A bachelor’s degree (or equivalent) from a regionally accredited college or university
- One short essay
- Essay topic: Please explain what has led you to pursue the Foundations in Business Analytics Certificate. How do you plan to apply the certificate to your career goals?
Application Deadlines
Next Deadline: November 27, 2019
Next Term Start: January 6, 2020
Have Questions?
We want to ensure you can take advantage of this opportunity to transition into a rewarding new analytics career. Feel free to schedule a call with an Admissions Advisor if you have any questions about the Online Foundations in Business Analytics Certificate, or about using it to transition into the Online MSBA program.
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Sources
1. Retrieved on September 27, 2019, from medium.com/@data_driven/python-vs-r-for-data-science-and-the-winner-is-3ebb1a968197
2. Retrieved on September 27, 2019, from techrepublic.com/article/top-5-tech-skills-data-scientists-need-and-how-to-learn-them/