two people looking at analytics on a laptop

Data Analytics Program

Audience: Professionals, executives, managers and administrators in every industry
Method: Online; meets 2 times weekly
Duration: 6 weeks
Cost: $1,250
Graduate application: Not required
Credits: Non-credit course (see note below)

Online Data Analytics Course

Learn in-demand tech skills by completing hands-on projects from top tech companies like Spotify, NetFlix and Airbnb in this course. Almost every industry from business to education, health care and nonprofit now requires employees who are able to use data to make better-informed decisions. Sharpen your data skills with this professional development program.

All lectures are 100% online, and you’ll meet virtually, two times each week with your classmates and instructor in a live discussion. Meeting times are Tuesday and Thursday from 6:30-8 p.m. 

Introduction to Applied Data Analytics

Learn applied job skills in close connection to the concepts and theories that drive the daily decisions relevant to data analysis and business intelligence. Each module will focus on a primary theme. Students will start by grappling with real-world cases, then will methodically drill down to solve the problems from a technical approach. Upon completing this course, you’ll be able to:

  • Understand implications of data bias in case studies
  • Understand different data types and use cases
  • Ask effective questions about the data
  • Understand business metrics and KPIs
  • Communicate technical information to business stakeholders
  • Understand the difference between supervised and unsupervised learning
  • Create a conversion rate optimization analysis
  • Create a customer experience analysis
  • Understand the differences between common data types in Excel
  • Demonstrate ability to calculate standard statistical measures in Excel
  • Demonstrate proficiency with common data analysis techniques in Excel, e.g., Pivot Tables and VLOOKUP
  • Create and interpret a linear regression model in Excel
  • Create and interpret a time series model in Excel
  • Implement logistic regression in Excel
  • Demonstrate ability with basic visualizations in Excel
  • Create and run a hypothesis test

A note on course credit

This is a professional development course, and it does not carry credit. However, individuals who successfully complete the course and then enroll in Creighton’s Master of Business AdministrationMaster of Science in Analytics or other closely related program may be eligible for up to three hours of awarded credit toward their degree.

Meet Your Course Instructor

Professor Alvarez is an Artificial Intelligence advisor to NASA. He has served as an adjunct Professor of Data Science and Machine Learning at Santa Clara University Leavey School of Business. He has also held a variety of industry data science roles at Intel and CERN. Additionally, he taught data science in an applied format for the leading Silicon Valley data science bootcamp.

REFUND POLICY

Continuing education and professional development courses may be cancelled by the attendee in writing up to 7 days before the course begins for a full refund, less a $25 processing fee. No refund will be given 7 days prior to the course. Some courses are not eligible for a refund; these exceptions are noted in specific course descriptions. In the event of a weather related closure, the course will be rescheduled.
 
Student interactions and viewpoints are a vital part of our rich learning environment. For this reason, Creighton reserves the right to cancel courses in the case of low registration numbers. In this case, registrants will receive a full refund. If a course is cancelled by the University for other non-weather related issues, the student will be notified and a full refund will be processed.

Questions?

If you have questions please fill out our Contact Us form or call 402.280.4076. We can also provide assistance with group registration or work with you to develop a customized course for a team.

Contact Us

This Course is Offered on the Following Dates

Nov. 30–Jan. 20; Online; Register by 11/25