Graduate Certificate
in Applied Analytics

Personalized Attention.
Professional Growth.
Community Impact.

Elevate your role or change your career by upskilling yourself with an advanced degree in Applied Analytics.

Learn how to increase profits and company growth with the power of data analysis.

Data-informed decision-making has permeated virtually all aspects of life, from health care to social services, business, politics, manufacturing, retailing, real estate, finance, insurance, and sports. The Master of Science in Applied Analytics and Graduate Certificate in Applied Analytics are designed to give working professionals the technical skills and management tools needed to make data-informed decisions.

Students will gain insights into discovering meaningful patterns in data and how predictive modeling can be used to improve decision-making. Loras College's Graduate Analytics programs will position your employees to make better decisions today and facilitate their increasing use of analytics in the future.

FLEXIBLE & CONVENIENT
Both the Master of Science in Applied Analytics and the Graduate Certificate in Applied Analytics programs are delivered through a blend of online and classroom delivery, integrating the flexibility of online learning without losing the valuable personal interaction that a classroom provides.

Depending on the program, students take either one or two courses at a time (comprised of a 14-week fully online course and/or a 7-week hybrid course). Each class is held just one night per week, allowing students to continue working while in school.

In the 7-week hybrid courses, the first six weeks are delivered online in a live virtual classroom, and in the last week students come together face-to-face for a full weekend on the beautiful Loras campus in Dubuque. On campus, students will hear from engaging speakers and participate in meaningful group work.

Applied Analytics Degree Comparison chart.pdf

ARE YOU READY?
Now is the time to invest, whether you’re looking to build your individual knowledge and skill-set or manage a business/organization and aim to motivate and inspire your current workforce through tuition reimbursement. You don’t have to be a large company to analyze, utilize, and benefit from big data. Our program is designed to immediately improve an organization’s use of data, and establish a baseline for future evolution.

Straight Talk from a Duhawk

Companies of all sizes are leveraging the power of intelligence from data, adding new value to their organizations. The applied analytics and machine learning offerings at Loras continue to raise the bar each year. Loras offers exceptional course content from professors with relevant industry experience. The cohort format enables strong networking relationships, while single course focus and less than one-year timeline are ideal for working professionals.

Joni Wallace, Associate Director of Artificial Intelligence, Collins Aerospace

Straight Talk from a Duhawk

"Offerings at Loras continue to raise the bar each year. Single course focus and less than one-year timeline are ideal for working professionals."

Read More

Straight Talk From an Employer

The utilization of data analytics helps us monitor the vital signs of the organization, to ensure it is operating healthy. In addition, the internal transparency and visibility of the performance of the organization helps with problem-solving, creates higher engagement levels among the employees, and has increased retention levels of our employees.

Brad Pinchuk, President and CEO,
Hirschbach

Straight Talk From an Employer

"Has increased retention levels of our employees"

Read More
Application Requirements

Graduate Certificate in Applied Analytics Program Application Checklists:

2020 Students Application Requirements 2021 Students Application Requirements

 

International Students Application Requirements

 

Course Requirements & Schedule

FALL 2020
Data Visualization (MAA 550)
Tuesday Nights online + 1 in-person weekend, Aug 29 – Oct 13
Data Science (MAA 520)
Tuesday Nights online + 1 in-person weekend, Oct 20 – Dec 13

JANUARY TERM 2021
Database Programming (MAA 521)
Tuesday & Wednesday Nights online + 1 in-person weekend, Jan 5 – Jan 31

SPRING 2021
Machine Intelligence (MAA 540)
Tuesday Nights online + 1 in-person weekend, Feb 2 – March 21
Marketing Analytics (MAA 560)
Tuesday Nights online + 1 in-person weekend, March 23 – May 16

Course Descriptions

MAA-520 Data Science (Fall)
Analytics is the process of taking data and turning it into new forms of value. The beginning of this process is often referred to as Data Science and the second stage of the process encompasses algorithms and visualization. As an introduction to data science, we proceed to cover practical data analytic skills including accessing and transferring data (ETL — extract, transform, load), applying analytical frameworks or patterns, applying methods from data mining and machine learning, and learning analysis methods for processing text. The course will also provide students an opportunity to do hands-on exercises with Big Data. The emphasis will be on practical usefulness and analytics patterns. 3 credits.

MAA-521: Database Programming (January Term)
This course explores the fundamental concepts of relational databases: how they are designed, accessed, protected, and managed.  The primary focus is on database programming – statements that retrieve, modify, summarize, analyze, and extract data. Storing of queries within the database for repeated use will be covered. 3 credits.s

MAA-540 Machine Intelligence (Spring)
Machine intelligence involves the set of technologies that permit computers to learn, including pattern recognition (text, image, and data), classification modeling, recommendation systems, natural language processing, and a variety of applications that increasingly are part of everyday life. Often referred to as “artificial intelligence,” this course goes further to explore techniques (such as recurrent neural networks and deep learning) which automate the ability of computers to recognize and identify patterns and learn from these. These techniques are scalable in ways that provide automatic implementation – ranging from web search algorithms to intelligent agents to self-driving cars. This course will provide hands-on experience building such systems, but with the focus on understanding the implications for business. Students will gain an appreciation for the scope of potential applications, the limits of machine intelligence, ethical aspects of their use, and disruptive tendencies of these technologies. 3 credits.

MAA-550 Data Visualization (Fall)
Data/Information visualization is widely used in a number of industries, including business, engineering, and media disciplines to help people analyze and understand what the data is telling us. The industry has grown exponentially over the last few years, and as a result there are more tools available to help us quickly and efficiently create compelling visualizations. This course provides an overview of the data/information visualization discipline. Using a hands-on approach, readings and lectures will cover various visualization principles and tools. Our labs will focus on practical introductions to tools and frameworks, with plenty of time to explore & utilize additional applications. We will discuss existing visualizations (e.g. what we find in various publications and government data sources) and critique their effectiveness in conveying information. All students are expected to participate in class discussion, complete lab assignments, and create & critique many data visualization examples throughout the session. 3 credits.

MAA-560 Marketing Analytics (Spring)
Marketing remains a branch of business as well as a social science, and is often characterized by the “4 Ps” of product, place, promotion, and price, and has been extended in many contexts to include people, packaging, and positioning. Each of these Ps is a candidate for improvement through the use of analytics. In Marketing Analytics, we consider the analytics of:

  1. Pricing, Forecasting Sales
  2. Understanding Customer Demand
  3. Customer Value
  4. Market Segmentation
  5. Retailing
  6. Advertising
  7. Market Research Tools
  8. Internet and Social Marketing.

Topics include, but are not limited to, Price Bundling, Willingness to Pay, Profile Conjoint Analysis, Discrete Choice Analysis, Value Templates, Clustering and Collaborative Filtering, Bass Diffusion Models, Market Basket Analysis, Pay-per-Click Advertising, Principal Components Analysis, Measuring Nodes and Links, Network Contagion, and Viral Marketing Models. 3 credits.

Frequently Asked Questions

Application and Admission FAQ

What are the academic requirements for admission into the Master of Science in Applied Analytics and Graduate Certificate in Applied Analytics programs?

  • A minimum cumulative GPA of at least 2.75 (or 2.9 in last 60 credits) of a completed bachelor’s degree.

How do I apply for admission?
Interested students may apply by completing the free online application (loras.edu/apply), uploading a current resume to their personalized online Application Tracker page, and having all official transcripts sent directly from the institution to:

Loras College Graduate Admission
Attn: Megan Henderson
1450 Alta Vista Street
Dubuque, IA 52001.

What is the application deadline?
Fall enrollment – all materials due by August 1.
Spring enrollment – please contact the Program Director to discuss class availability and your eligibility for a Spring start.

Applications submitted after the deadline will be considered on an individual basis.

Do either the Master of Science or Certificate program require any particular undergraduate degree?
Students are eligible for either program regardless of their undergraduate major. Programming knowledge/experience is not required, but familiarity with statistics is beneficial. It’s a myth that you need to be an expert in math or programming in order to effectively analyze data. Programming is useful for doing data analysis, but not necessary. Nor is it sufficient. Using data to improve decision-making requires actionable insight. This means understanding where analytics can improve decisions, obtaining the appropriate data, understanding what it does/does not measure, shaping it into an appropriate form, building useful predictive or explanatory models, and communicating the insight to multiple audiences: customers, employees, owners, communities, and beyond. Actionable insight also requires using your existing knowledge to ask the tough questions needed to move your organization or business forward. Loras’s graduate analytics programs are designed to provide and sharpen this skill-set for working professionals.

How long will it take to receive an admission decision regarding my application?
Immediately following receipt of all application materials, your file will be reviewed by the Program Director and you will be notified of an admission decision within one week.

How will I be notified of the admission decision?
You will be contacted by email once a decision has been made.

How can I receive more information about the Master of Science in Applied Analytics or Certificate in Applied Analytics program?
For more information about the program curriculum, please contact James Padilla, J.D., Francis J. Noonan School of Business Dean, at: james.padilla@loras.edu or 563.588.7405. For more information about the application and admission process, please contact Megan Henderson, Director of Admission for Graduate and Postbaccalaureate Programs, at: megan.henderson@loras.edu or 563.588.7140.

Curriculum and Class Format FAQ

How many credits are required?
A total of 15 credits are needed to meet the course requirements for the Graduate Certificate in Applied Analytics, and a total of 30 credits are required for the Master of Science in Applied Analytics degree.

What is the class format?
Our programs are delivered through a blend of online and classroom delivery, integrating the flexibility of online learning without losing the valuable personal interaction that a classroom provides. Students take either on or two 7-week courses at a time and each class is held just one night per week. The first six weeks are delivered online in a live virtual classroom. During the final week, students come together face-to-face for a full weekend on the beautiful Loras campus in Dubuque. On campus, students will hear from engaging speakers and participate in meaningful group work.

How long does it take to complete the programs?
The Certificate can be completed in 9 months (Sept.-May), and the Master of Science degree can be completed in one year (Sept.–Sept.).

Is there a preferred entry point into the programs?
Both programs begin in the Fall semester. Students interested in a Spring start should contact the program director to discuss their eligibility and class availability.

Does either program accept transfer credits?
We do not accept transfer credits into the certificate program, but students may transfer in up to 9 credits into the Master of Science in Applied Analytics degree. Please consult the Graduate Bulletin for details.

What is the time commitment outside of class?
Time commitments vary depending on the course and individual’s specific skill set. As a general rule, students will spend 4 – 6 hours per week outside of classroom instruction on class-related work for each class.

Where are classes held?
The face-to-face weekend classes are held on the beautiful Loras College campus on the 3rd floor of Keane Hall.

When do classes meet?
Each online live class meets one or two evenings per week, typically from 6:30pm – 8:30pm. The face-to-face weekends typically meet on Saturday from 8am-5pm and on Sunday from 9am-5pm. For specific times and dates, see the course schedule prior to each academic semester.

Will there be an orientation prior to the first class?
Yes, students are required to attend the New Graduate Student Orientation prior to beginning coursework so they can become familiar with the faculty, campus, services and their peers.

Is Loras College accredited?
Yes, Loras College is accredited by the Higher Learning Commission of the North Central Association of Colleges and Schools.

Financial FAQ

What are current tuition rates for the Master of Science in Applied Analytics and the Graduate Certificate in Applied Analytics programs?
Visit the Graduate section of our Tuition & Fees page for detailed cost information.

Tuition and Fees are subject to change at any time.

Is financial aid available?
Federal aid is available for the Master of Science in Applied Analytics program, but not for the Graduate Certificate in Applied Analytics. Students who wish to obtain a Federal Direct Unsubsidized Loan must complete the current year FAFSA and take at least 3 credits per term. For more information, please contact our Financial Planning Office at 563-588-7136 or by email at financial.planning@loras.edu.

Tuition & Fees

Program Cost

Employer Reimbursement

  • The Employer Reimbursement Form must be completed.
  • Students are responsible for providing the course information, final grades, and billing information to their employer to obtain the reimbursement.
  • If the employer reimbursement criteria is not met and/or reimbursement is denied, the student must bring their account current before any future registration will be permitted.

Federal Loan Options (for Master of Science program only)

  • Students who wish to obtain a Federal Direct Unsubsidized Loan must complete the current year FAFSA and take at least 3 credits per term.
  • The loan will disburse directly to the school to cover the cost of the term.
  • Graduate students are eligible for up to $20,500 in loan funds each academic year.
  • The Liras College academic year runs from Summer-Spring (i.e. Summer 2020-Spring 2021).

Feel free to contact us if you have Billing Questions

Tuition and Fees are subject to change at any time.

Applied Analytics Faculty

James Padilla, J.D.
Francis J. Noonan School of Business Dean
563.588.7405 | james.padilla@loras.edu
Full Profile

Dale Lehman, Ph.D.
Center for Business Analytics Director
Professor of Business
563.588.7725 | Dale.Lehman@loras.edu
Full Profile

Robert Keller, Ph.D.
Division of Mathematics, Engineering, & Computer Science Chair
Professor of Mathematics
563.588.7015 | Robert.Keller@loras.edu
Full Profile

Roman Ciapalo, Ph.D.
Professor of Philosophy
563.588.7434 | Roman.Ciapalo@loras.edu
Full Profile

Shikhar Acharya
Assistant Professor of Business Analytics
563.588.7784 | shikhar.acharya@loras.edu
Full Profile

Questions? Let’s get in touch.

Loras College Graduate Admissions
Megan Henderson

megan.henderson@loras.edu
563.588.7140

Connect with us social media.

LinkedIn Icon