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Certificate in Predictive Business Analytics

The Predictive Business Analytics Certificate Program uses real-world problems and situations to prepare professionals for roles as strategic practitioners who leverage predictive analysis and predictive modeling to drive smart business decisions.

Predictive Business Analytics

Program Courses

To earn a certificate in Predictive Business Analytics, you must complete the four core courses and one elective.  




Professional Development Programs

Bridge School
PRED_BUS 200-DL Foundations in Statistics *Core Course

In this age of data explosion, a business is successful only when it is able to make sense of the data at its disposal. Statistics is instrumental in transforming numbers into useful information for decision makers at all levels. This course introduces students to basic statistical concepts to be used as a foundation of business analytics. Descriptive Statistics are the methods that discuss data collection, summarization and presentation. Statistical Inference is the collection of methods that interprets data collected from a small group and extends understanding to a larger group. This course introduces students to numerical and visual summarization of data, introductory probability, common probability distributions, sampling distribution and basic concepts of statistical inference Applications of statistics in business decision making are emphasized through case studies and data analysis. Discussion questions are provided with the goal of facilitating logical thinking and taking quantitative approaches towards solving business problems. Appropriate use of statistical techniques and correct interpretation of statistical findings in business analytics are vital in order to help business make sense of data. This course will help students in developing basic understanding of statistics and drawing inferences based on data. This course will also prepare the pathway for students to delve into big data and predictive analytics in the next modules of the course.

Spring 2017 Sec #14 (200-DL)
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Schedule Notes:

Cohort 14

 

This course begins on Saturday, April 22. Late registration will remain open until Saturday, April 29.

Start/End Dates Course Sync Time Building
04/29/17 - 05/13/17 Asynch
Instructor Course Format Status CAESAR Course ID
Online Open 38590
PRED_BUS 201-DL Introduction to Business Analytics *Core Course

This course focuses on building the programming and analytics skills necessary to build analytics solutions to business problems. The course begins with a general introduction to the subject of business analytics: what it is, how does it add value in an organization, and what are characteristics of organizations which successfully use analytics to drive operations. Using that as a foundation for later thought and action, the course moves into the fundamentals of programming using the mathematical and analytics language R. Through a mix of online content and student activities, the concepts of how to program in R are delivered. Students perform weekly activities including discussion boards, quizzes and assignments as well as exploration of the larger online data science and analytics community to prepare for applying analytics to business scenarios. The course wraps up with application of the analytics skills to reading and understanding business cases and a review of how hypothesis testing can be applied in business situations to promote better operations and results.

Spring 2017 Sec #13 (201-DL)


Schedule Notes:

Cohort 13

Start/End Dates Course Sync Time Building
03/05/17 - 05/07/17 Asynch
Instructor Course Format Status CAESAR Course ID
Online Closed 37972
Spring 2017 Sec #14 (201-DL)


Schedule Notes:

Cohort 14

 

This course begins on Saturday, May 27. Late registration will remain open until Saturday, June 3.

Start/End Dates Course Sync Time Building
06/03/17 - 07/15/17 Asynch
Instructor Course Format Status CAESAR Course ID
Online Closed 38591
PRED_BUS 202-DL Modeling Methods *Core Course

This course introduces students to applying predictive models in business areas such as marketing, finance, supply chain, etc. The course aims to provide a hands-on approach to teach students about models that are frequently applied to make informed business decisions. Students will learn regression and classification methods – based on ordinary least squares based regression, logistic regression, and multinomial logit, and classification and regression trees. Student will learn how to implement these methods in the R statistical programming language. The course format is a combination of textbook readings, Video sessions, group discussions, in-class and online lectures from faculty. Weekly quizzes and programming assignments using R will be used to reinforce both concepts and practice.

Spring 2017 Sec #13 (202-DL)


Schedule Notes:

Cohort 13

 

This course begins on Sunday, May 21. Late registration will remain open until Sunday, May 28.

Start/End Dates Course Sync Time Building
05/28/17 - 07/09/17 Asynch
Instructor Course Format Status CAESAR Course ID
Online Closed 37973
Summer 2017 Sec #14 (202-DL)


Schedule Notes:

Cohort 14

 

This course begins on Saturday, July 29. Late registration will remain open until Saturday, August 5

Start/End Dates Course Sync Time Building
08/05/17 - 09/23/17 Asynch
Instructor Course Format Status CAESAR Course ID
Online Closed 41711
PRED_BUS 203-DL Advanced Modeling Methods *Core Course

Advanced Modeling Methods gives business analysts the foundation and tools to implement various prediction algorithms that will allow them to make better data driven decision for their business. This course places emphasis on modeling techniques to gain insight into hidden data patterns while using the technology stack of R. Topics covered will include various classification algorithms such as Cluster Analysis, Neural Networks, Discriminant Analysis, and Support Vector Machines. Students will also be introduced to various topics in Time Series, and other statistical based methods including Principal Component Analysis and Affinity Analysis. Lastly, students will learn about the structure of Networks and how tools such as Sentiment Analysis can provide valuable insight into their customer base.

Spring 2017 Sec #12 (203-DL)


Schedule Notes:

Cohort 12

 

This course begins Sunday, March 19. Late registration will remain open until Sunday, March 26.

Start/End Dates Course Sync Time Building
03/26/17 - 05/14/17 Asynch
Instructor Course Format Status CAESAR Course ID
Online Open 37974
Summer 2017 Sec #13 (203-DL)


Schedule Notes:

Cohort 13

 

This course begins on Sunday, July 23. Late registration will remain open until Sunday, July 30.

Start/End Dates Course Sync Time Building
07/30/17 - 09/10/17 Asynch
Instructor Course Format Status CAESAR Course ID
Online Closed 41712
PRED_BUS 204-DL Analytics Communication & Management *Core Course

In this section we will focus the keys to becoming a predictive analytics enabled organization. Next we will examine how to take the results from data mining and predictive analytics to create powerful and convincing visual analytics. We will focus on creating info graphics, PowerPoint presentations, Dashboarding software and writing simple code in R to create powerful charts and infographics. We will also learn methods to create lasting impact on the audience while designing such infographics, visuals and dashboards. We will learn different examples from the industry on the best practices. Lastly, we will examine how an organization can use predictive analytics as a competitive advantage and the privacy and security concerns that may accompany that transformation.

Spring 2017 Sec #12 (204-DL)


Schedule Notes:

Cohort 12

 

This course begins on Sunday, May 28. Late registration will remain open until Sunday, June 4.

Start/End Dates Course Sync Time Building
06/04/17 - 07/16/17 Asynch
Instructor Course Format Status CAESAR Course ID
Online Closed 37975