Master of Science
in Applied Analytics

Personalized Attention.
Professional Growth.
Community Impact.

Learn how to apply the latest methods and technologies to help your organization gather, store, report, and analyze important data

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. Loras College's fully online Master of Science in Applied Analytics degree was designed by an impressive consortium of analytics leaders, and gives working professionals the technical skills and management tools needed to make data-informed decisions, and make an immediate positive impact at their jobs.

Loras’ degree is truly applied in the sense that the program is built around “learning by doing.”  Students learn to handle data knowledgably by working with data through project-oriented learning, building conceptual understanding as well as critical technical skills and proficiency as they do so.  This program sources many of its projects from community partners — actual data from organizations and businesses in the region — and students in the program are motivated not only by the authenticity of the projects but also because students see real value in improving the world in which we live.  

ARE YOU READY?
Whether you are looking to enhance your own individual skillset, or you manage a business/organization and want to motivate your current workforce through tuition reimbursement, now is the time to invest!

You don’t have to work at a large company to analyze, utilize, and benefit from big data. Our program is designed to immediately improve any organization’s use of data, establish a baseline for future evolution, and position you or your employees to make better decisions today and facilitate the increasing use of analytics and predictive modeling in the future.

FLEXIBLE & CONVENIENT
Classes are offered in a convenient live online format and each class is held just one night per week, allowing students to continue working while in school. Our flexible scheduling allows students to either begin in the Fall (with an option to complete the program in one year or two years), or Spring (with a 15-month completion timeline).

LEARN MORE WITH A GRAD CHAT
Loras is pleased to offer an opportunity for prospective graduate Applied Analytics students to enjoy a casual, personalized Zoom conversation with the Applied Analytics Program Director and the Director of Graduate Admission to learn more about the curriculum, industry job outlook, enrollment process, and much more. Get a true sense of what grad school is like from a faculty member you will be working closely with.

Grad Chat Registration

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."

MEET JONI

Straight Talk from a Duhawk

“I am grateful for the great education and experience I received from Loras’s graduate analytics degree.

The extra touch of statistical modeling and economics expertise that the faculty bring gives the program a technical feel, and for me, brought a world of interest I had not explored before. Loras’s lineup of professors were strong in their fields and provided a variety in both subject matter and style. The students in our cohort also contributed to making the experience great and I look forward to long-standing relationships with them.”

John Unsen, Vice President of Systems
VGM Insurance Services

Straight Talk from a Duhawk

"The analytics program provides a full foundational understanding of business analytics while also running the gamut of executive-level business skills and proficiencies."

MEET JOHN

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"

MEET BRAD
Admission Criteria & Application Checklist

Admission Criteria and Eligibility Information:

The M.S. in Applied Analytics is designed to provide and sharpen this skill-set for working professionals. Students are eligible for this degree 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.

    Application Checklist- Domestic Student

    Application Checklist- International Student

    Course Requirements & Schedule

    Loras offers scheduling options for either a 1 or 2 year completion plan with a Fall start, or a 15-month completion plan with a Spring start.

    Fall Start: One Year Program Completion Plan »

    Students take two courses at a time (one 14-week course and one 7-week course) and therefore will be in class two nights per week, plus a weekend component at the end of each 7-week class. Students will also take one 4-week course in January.

    All classes are held online in a live, virtual format. Please see the “Course Listings/Schedule” section of the Registrar’s Office webpage for specific course dates: https://www.loras.edu/academics/registrar/

    14-week course format:
    Weeks 1-14: class meets online one night per week for two hours.

    7-week course format:
    Weeks 1-6: class meets online one night per week for two hours.
    Week 7: class meets online on Saturday and Sunday for three hours each day.

    January Term course format:
    Weeks 1-4: class meets online two nights per week for two hours each night.
    Week 5: class meets online on Saturday and Sunday for three hours each day.

    FALL
    Risk Analysis (MAA 571): 14 weeks
    Data Visualization* (MAA 550): 7 weeks
    Database Programming (MAA 521): 7 weeks

    JANUARY TERM
    Ethical/Social Responsibilities of Data Analysis (MAA 515): 4 weeks

    SPRING
    Programming for Analytics Methods (MAA 530): 14 weeks
    Data Science* (MAA 520): 7 weeks
    Machine Intelligence* (MAA 540): 7 weeks

    SUMMER
    Capstone Seminar (MAA 581): 14 weeks
    Big Data Ecosystem (MAA 509): 7 weeks
    Marketing Analytics* (MAA 560): 7 weeks

    *Indicates the 4 courses required for the Graduate Certificate in Applied Analytics. The 5th course is an elective of your choosing. The Certificate can be completed in one year with one course at a time. 

    Fall Start: Two Year Program Completion Plan »

    Students take one course at a time (either one 7-week course or one 14-week course) and therefore will be in class one night per week, plus a weekend component at the end of each 7-week class. Students will also take one 4-week course during a January Term. 

    All classes are held online in a live, virtual format. Please see the “Course Listings/Schedule” section of the Registrar’s Office webpage for specific course dates: https://www.loras.edu/academics/registrar/

    7-week course format:
    Weeks 1-6: class meets online one night per week for two hours.
    Week 7: class meets online on Saturday and Sunday for three hours each day.

    14-week course format:
    Weeks 1-14: class meets online one night per week for two hours.

    January Term course format:
    Weeks 1-4: class meets online two nights per week for two hours each night.
    Week 5: class meets online on Saturday and Sunday for three hours each day.

    FALL
    Data Visualization* (MAA 550): 7 weeks
    Database Programming (MAA 521): 7 weeks

    JANUARY TERM
    Ethical/Social Responsibilities of Data Analysis (MAA 515): 4 weeks (can also be taken during January Term in Year 2 instead)

    SPRING
    Data Science* (MAA 520): 7 weeks
    Machine Intelligence* (MAA 540): 7 weeks

    SUMMER
    Big Data Ecosystem (MAA 509): 7 weeks
    Marketing Analytics* (MAA 560): 7 weeks

    FALL
    Risk Analysis (MAA 571): 14 weeks

    JANUARY TERM
    no class

    SPRING
    Programming for Analytics Methods (MAA 530): 14 weeks

    SUMMER
    Capstone (MAA 581): 14 weeks

    *Indicates the 4 courses required for the Graduate Certificate in Applied Analytics. The 5th course is an elective of your choosing. The Certificate can be completed in one year with one course at a time. 

    Spring Start: 15-month Program Completion Plan »

    Students take one or two courses at a time, depending on the semester, and therefore will be in class one or two nights per week, plus a weekend component at the end of each 7-week class. Students will also take one 4-week course in January.

    All classes are held online in a live, virtual format. Please see the “Course Listings/Schedule” section of the Registrar’s Office webpage for specific course dates: https://www.loras.edu/academics/registrar/

    14-week course format:
    Weeks 1-14: class meets online one night per week for two hours.

    7-week course format:
    Weeks 1-6: class meets online one night per week for two hours.
    Week 7: class meets online on Saturday and Sunday for three hours each day.

    January Term course format:
    Weeks 1-4: class meets online two nights per week for two hours each night.
    Week 5: class meets online on Saturday and Sunday for three hours each day.

    SPRING
    Programming for Analytics Methods (MAA 530): 14 weeks
    Data Science* (MAA 520): 7 weeks
    Machine Intelligence* (MAA 540): 7 weeks

    SUMMER
    Big Data Ecosystem (MAA 509): 7 weeks
    Marketing Analytics* (MAA 560): 7 weeks

    FALL
    Risk Analysis (MAA 571): 14 weeks
    Data Visualization* (MAA 550): 7 weeks
    Database Programming (MAA 521): 7 weeks

    JANUARY TERM
    Ethical/Social Responsibilities of Data Analysis (MAA 515): 4 weeks

    SPRING
    Capstone Seminar (MAA 581): 14 weeks

    *Indicates the 4 courses required for the Graduate Certificate in Applied Analytics. The 5th course is an elective of your choosing. The Certificate can be completed in one year with one course at a time. 

     

    Course Descriptions

    Individuals who would like to take some graduate courses for professional development, continuing education credits, or just personal enrichment may take up to 9 graduate credits as a non-degree special student. Learn more

    MAA-509 Big Data Ecosystem
    This course examines the data management process from access to data sources through implementation of scalable processes. Big data requires understanding database design, and increasingly involves parallel processing and cloud-based data storage and analysis. Data formats and database architectures are examined. Tools for extracting data from relational, structured, and non-structured databases are explored. Included are issues related to data security and governance. Students will also learn how to evaluate technologies used to implement scalable decision analytic systems. 3 credits.

    MAA-515 Ethical and Social Responsibilities of Data Analysis
    This course consists of two parts. In the first, relatively brief part, we examine the ethical principles and theories that are relevant to resolving any moral issue. In the second part, we apply these principles and theories to the key moral issues in business (with emphasis, where appropriate and relevant, on questions dealing with data/information acquisition, analysis, and application) by studying, discussing, and debating them, principally through a case-study approach. The focus of our attention is on the three basic kinds of moral relationships in business: a) between the firm and the employee; b) between the firm and other economic agents (i.e., customers, competitors); and c) between the firm and various non-business groups (i.e., the environment). 3 credits.

    MAA-520 Data Science
    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
    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.

    MAA-530 Programming for Analytic Methods
    Business Analytics is the process of transforming data into business value. The Data Science course explores a variety of analytical methods for building models (predictive or explanatory). This course will focus on programming languages used for accessing, analyzing, and implementing such models. While many software platforms are available to automate various parts of this process, programming languages are commonly used – primarily R and Python at present. This course exposes students to the use of these languages, focusing on their use for accessing and cleaning data sources and implementing models in a production environment. The subsequent course (Big Data Ecosystem) utilizes these languages for an understanding of the entire process of Business Analytics. While some students may develop a proficiency with coding in these programming languages, the purpose of the course is to provide sufficient exposure to the use of these languages for making business decisions regarding choices of software, human resources, and organizational structures necessary for developing Business Analytics efforts. 3 credits

    MAA-540 Machine Intelligence
    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
    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
    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.

    MAA-571 Risk Analysis
    An important part of business planning is identification, analysis, and management of risk. This spreadsheet-based course examines a variety of models geared to addressing business and social needs. Uncertainty is explicitly analyzed through the use of scenarios, simulation, and other techniques. Emphasis is placed on understanding and communicating the important uncertainties associated with any plan, and developing ways to incorporate these into business plans. 3 credits.

    MAA-581 Capstone Seminar
    The goal of this course is to have students complete a data project (generally in groups) of a complex nature. This includes obtaining and cleaning relevant data, conducting appropriate analysis and communications of findings, and planning implementation of organizational processes that utilize the results of the project. Projects may come from students’ work environment, Center for Business Analytics sponsored projects, or other timely data projects that may arise at appropriate times. 3 credits.

    Frequently Asked Questions

    Application and Admission

    What are the academic requirements for admission into the Master of Science in Applied Analytics program?
    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?
    Please see the Admission Criteria & Application Checklist section of this webpage.

    What is the application deadline?
    Fall enrollment – all materials due by August 1.
    Spring enrollment – all materials due by January 1.

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

    Does the Master of Science program require any particular undergraduate degree?
    Students are eligible for this 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.

    Can I take some courses as a non-degree student?
    Individuals who would like to take graduate classes for professional development, continuing education credits, or personal enrichment may take up to 9 graduate credits as a non-degree (Special) student. Special students may not enroll in practicum, clinical, internship courses or other courses without approval from the program director.

    In order to enroll in the course(s):

    1. Complete the free Loras College Special Course Application. Select “Graduate Course” as the Course Registration Type. You will need to upload copies of your unofficial transcript(s) from each college/university attended before submitting the application.
    2. The transcripts will be evaluated by the Program Director to ensure that any necessary pre-requisite course requirements have been met.
    3. After review of the transcript(s), the Registrar’s Office will be in touch with information about your next steps.
    • Please note that enrolled degree-seeking students have registration preference if a course is full.
    • After the completion of 9 non-degree credits, a student must then apply for formal admission into the graduate program in order to move forward and take additional courses.
    • Graduate courses completed by a “Special” student with a grade of B or better may be applied to a future graduate degree at Loras College with the approval of both the Program Director and the Academic Dean.
    • Financial aid is not available to non-degree “Special” students.
    • Students interested in any of Loras’ Professional and Continuing Education programs should refer to the individual program webpage for application and enrollment instructions.

    How can I receive more information about the Master of Science in Applied Analytics program?
    For more information about the program curriculum, please contact Dr. Robert Keller, Program Director, at robert.keller@loras.edu. For more information about the application and admission process, please contact Megan Henderson, Director of Admission for Graduate and Professional Education Programs, at: megan.henderson@loras.edu or 563.588.7140.

    Curriculum, Class Format, and Benefits

    How would earning this degree advance my career trajectory and salary potential?
    Graduates of the program stand out in their abilities to competently handle data and provide timely and insightful recommendations regarding both tactical operations as well as strategic initiatives. Those in C-suite level positions readily recognize the critical need for such employees, especially those who not only know how to answer, but also ask good questions.

    Can you share a specific example of a capstone project a student in this program has completed to show the practical application of the subject?
    Previous capstone projects include: exploring food insecurity in the greater Dubuque region, analyzing student performance data for a school district, and a project for 7 Hills Brewery that started with the basic question: “Nationally, there is some momentum to raise the minimum wage. Using data from 7 Hills, can we validate or refute the hypothesis that restaurants and similar business can adapt to this significant change?”

    How many credits are required?
    A total of 30 credits are required for the Master of Science in Applied Analytics degree.

    What is the class format?
    Classes are held in a convenient live online format and each class is held just one night per week, allowing students to continue working while in school. Our flexible scheduling allows students to either begin in the Fall (with an option to complete the program in one year or two years), or Spring (with a 15-month completion timeline). For more details about specific class times, please see the “Course Requirements and Schedule” section of this webpage.

    What kind of technology do I need to participate in the program?
    To participate effectively in the online graduate Analytics program, you will need a computer that is able to run video conferencing (including a working camera and microphone) and has an up-to-date operating system, as well as a stable high-speed internet connection.

    How long does it take to complete the programs?
    The Master of Science degree can be completed in either one year or two years (Fall start) or 15 months (Spring start).

    Does this program accept transfer credits?
    Students may transfer in up to 9 graduate 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.

    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.

    If I’m interested in playing a sport at Loras while in graduate school, how many credits do I have to take?
    Graduate students must be enrolled in a degree-seeking master’s program to be eligible to participate in NCAA athletics at Loras.

    Student athletes enrolled in one of our degree-seeking master’s programs need to have full-time status (taking at least 6 credits per term) during the semester(s) they’re practicing or competing in the sport. Students also need to be making satisfactory progress towards their degree (as determined by Loras). If a student wants to participate in athletics while being enrolled less than full-time, they will need to work with their coaches to determine if they are eligible for a waiver.

    Please note that while 6 credits per term is considered full-time for graduate students at Loras, students only need to take at least 3 credits per term in order to be eligible for federal financial aid.

    Financial

    What are current tuition rates for the Master of Science in Applied Analytics program?
    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?
    Degree-seeking graduate students (enrolled in a master’s program) are eligible to receive $20,500 in Federal Direct Unsubsidized Loan funds for each academic year. Students may choose to accept all or just part of the $20,500 amount. To obtain a loan, students must complete the FAFSA (Free Application for Federal Student Aid) each year at: https://studentaid.gov/ and take at least 3 credits per term. Loras’ school code is 001873.

    The loan will disburse directly to Loras to cover the cost of the term(s). For financial aid purposes, Loras’ academic year runs from summer-spring (ie: summer 2022 through spring 2023). Please be sure to complete the correct FAFSA for the term(s) you wish to receive loans. For example, students beginning a graduate program in summer 2022 would complete the 2022-2023 FAFSA.

    Loras College does not offer institutional scholarships or federal grants for graduate and professional education students at this time.

    Information about private loans can be found at: https://choice.fastproducts.org/FastChoice/home/187300/1

    Students who have outstanding loans from their undergraduate education may be able to defer payment on those loans while enrolled in a degree-seeking master’s program. Deferment options are generally available to students who are enrolled at least half-time in a graduate program (3 credits or more per semester). If deferment is a requirement for you to be able to afford to enroll in a graduate program, we advise you to connect with our Financial Planning Office or your loan service providers to make sure you know exactly how deferment applies to your previous loans.

    Program Cost and Financial Aid

    Master of Science in Applied Analytics Program Cost
    Visit the Graduate section of our Tuition & Fees page for detailed cost information.

    Employer Reimbursement
    Students who wish to utilize tuition reimbursement from their employer must complete Loras’ Employer Tuition Reimbursement Form before the first day of their first class. Students will still be issued regular billing statements from Loras, but will be exempt from any service charges and will be exempt from having to make full payment until after the end of each class (or until after program completion for CFP Certification or Cybersecurity Bootcamp students). Students or employers are welcome to make payments directly to Loras along the way if they would like, but it is not required. If the employer reimbursement criteria are not met and/or reimbursement is denied, the student must bring their account current immediately before any future registration will be permitted. Student’s balance must be paid in full within 30 days of the last day of each term (or within 30 days of program completion for CFP Certification Education and Cybersecurity Bootcamp students), and prior to Loras issuing the student a degree and/or final transcript.

    Financial Aid
    Degree-seeking graduate students (enrolled in a master’s program) are eligible to receive $20,500 in Federal Direct Unsubsidized Loan funds for each academic year. Students may choose to accept all or just part of the $20,500 amount. To obtain a loan, students must complete the FAFSA (Free Application for Federal Student Aid) each year at: https://studentaid.gov/ and take at least 3 credits per term. Loras’ school code is 001873.

    The loan will disburse directly to Loras to cover the cost of the term(s). For financial aid purposes, Loras’ academic year runs from summer-spring (ie: summer 2022 through spring 2023). Please be sure to complete the correct FAFSA for the term(s) you wish to receive loans. For example, students beginning a graduate program in summer 2022 would complete the 2022-2023 FAFSA.

    Loras College does not offer institutional scholarships or federal grants for graduate and professional education students at this time.

    Information about private loans can be found at: https://choice.fastproducts.org/FastChoice/home/187300/1

    Students who have outstanding loans from their undergraduate education may be able to defer payment on those loans while enrolled in a degree-seeking master’s program. Deferment options are generally available to students who are enrolled at least half-time in a graduate program (3 credits or more per semester). If deferment is a requirement for you to be able to afford to enroll in a graduate program, we advise you to connect with our Financial Planning Office or your loan service providers to make sure you know exactly how deferment applies to your previous loans.

    Contact us if you have additional financial aid or billing questions:
    Financial Planning Office
    Financial.planning@loras.edu
    563.588.7136

    Carrie Jones, Director of Student Accounts
    Carrie.jones@loras.edu
    563.588.7232

    Tuition and Fees are subject to change at any time.

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    Corporate Partnerships

    Questions? Let’s get in touch.

    Loras College Graduate Admissions
    Megan Henderson

    megan.henderson@loras.edu
    563.588.7140

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