Data-Driven Decision-Making Professional Certificate

Learn a variety of analytics techniques and software tools to improve your ability for data-driven decision-making and to effectively communicate with data science teams.

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Develop critical decision-making and problem-solving skills

In today’s analytics-based world, business professionals need data-driven decision-making skills to interpret data effectively and make informed decisions. This practical, online, decision science course introduces essential analytical techniques tailored for real-world business applications.

You’ll begin with the fundamentals of data interpretation, learning to understand distributions and relationships within data sets. Next, tackle uncertainty in business contexts using Monte Carlo simulations, then explore methods for optimizing decisions to achieve your business goals. The course wraps up by guiding you through developing predictive models based on historical data to anticipate trends and make proactive decisions.  

This 10-week course is completed in a self-paced format and includes optional live sessions with an expert instructor, offering personalized guidance to help you apply your new skills directly to your work. Upon successful completion, you’ll earn data-driven decision-making certification issued by the IU Kelley School of Business, demonstrating your enhanced data analytics capabilities.

Accreditations: Continuing Education Credits Eligible/.6 CEUs per course/3.0 CEUs per certificate

Upcoming dates and certificate overview

Dates: August 4 to October 6
Price: $2,550
Duration: 10 weeks, three to four hours per week
Delivery: Online

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Showcase your new skills

Data-Driven Decision Making badge

In addition to earning a professional certificate upon completion of this program, you will also earn a digital badge to showcase your skills on platforms like LinkedIn. These credentials show your network the concrete and in-demand skills you earned from taking this Kelley program.

Decision science course topics

  1. Introduction to Data and Predictive Analytics
  2. Introduction to R and R Studio
  3. Prepping Data for Analysis
  4. Data Visualization
  5. Linear Regression Models
  6. Logistic Regression Models
  7. PCA, Factor Analysis, and Cluster Analysis
  8. Neural Networks and K-nearest Neighbors

 

Learning outcomes

This program will consist of 10 webinars and will include both practical exercises and quizzes. At the conclusion of the course, students will be able to construct, validate, and interpret data mining and predictive analytics models using large data sets, and apply these techniques to marketing, finance, and operations problems. Students will complete weekly quizzes to demonstrate mastery of the subject matter and to qualify for the certificate. Upon completion of the program, students will receive a digital badge to share on their resume, LinkedIn profile, and other sites.

 

Summer 2025

Class start date: May 12
Live session dates: May 21, June 4, June 18, July 2, July 16

Fall 2025

Class start date: August 4
Live session dates: August 13, August 27, September 10, September 24, October 8

Meet the instructor

John D. Hill

John D. Hill, MBA, PhD, is a Grant Thornton Scholar in the Department of Operations & Decision Technologies at the Kelley School of Business in Bloomington, Indiana, where he has taught for 12 years in the Full-Time +Flex MBA Program. He has won several teaching awards at Kelley, including the Innovative Teaching Award, the Eyster Teaching Scholar Award, and multiple MBA Teaching Excellence Awards.

Questions? We're here to help.

Email us at kelleypd@iu.edu with any questions you may have, and a member of our team will be happy to assist you.