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Master of Science in Analytics
Analytics
Sharpen your focus as an IT professional and become a leader in the field of analytics. Our online MS in Analytics can help you develop your command of powerful analytic tools to support successful businesses in today’s competitive landscape. This program helps you master advanced skills in data mining, statistics, applied analytics, modeling, forecasting, and more. You’ll learn how to find, interpret and use key information to drive effective decision-making in organizational settings.
Classes start July 12
Use the code SPRING to waive the $50 application fee.
At a Glance
- Online
- 11 Core courses
- Capstone
- 48 Total quarter credits (12 max transfer credits)
Reduce your tuition by $3,000
Enroll in a qualified program and apply for a $3K Capella Progress Reward, a scholarship to help fund your master’s degree.
Admission Requirements
Applicants to the MS in Analytics program must provide the following information for admission:
- Bachelor’s degree from an institution accredited by a U.S. Department of Education-recognized accrediting agency or an internationally recognized institution
- Your official bachelor’s transcripts, minimum grade point average of 2.3 or higher on a 4.0 scale
- A $50 nonrefundable application fee, required at the time of application, to cover transcript requests, transcript evaluation, and other administrative costs
- A background acknowledgement form that indicates your technology degree or relevant work requirements for this program
- A valid, government-issued form of photo identification
GRE and GMAT are not required for admission.
International student requirements
If you completed your most recent academic coursework, degree, or credential at an institution outside the United States, regardless of your citizenship or where you currently live, you are considered an international applicant.
In addition to the above admission requirements, you will need to submit these materials:
- Minimum score on acceptable test for proof of English proficiency
- Transcript evaluation
Learn more about international student admissions.
A structured learning format with an active peer community and faculty guidance. We’ll set the schedule, you meet the deadlines.
- Based on the quarter system; 1–3 courses per 10-week quarter
- 1 semester credit = 1.5 quarter credits
- Weekly assignments and courseroom discussions
- Pay for what you take, price varies by courseload or term
$25,020–$33,360*
MAX TRANSFER CREDITS–TYPICAL TRANSFER CREDITS
$695 per credit, 48 total quarter credits, 12 max transfer credits
*This is only an estimate, using general program pricing, and it does not include fees (including application and resource kit fees). Your price may be higher or lower depending on your specialization, transfer credits, and tuition discounts. If transfer credits are allowed in this offering, the prices above show what you would pay if you brought in the average number of transfer credits and the price if you brought in the maximum allowed transfer credits.
Questions about cost?
Contact an enrollment counselor.
“Working full time as a Network Technician meant I needed to take classes at times that would work for me. Capella checked off all the boxes! The flexibility was outstanding.”
Will Resendes* – BS IT
*Actual Capella student who agreed to appear in promotional materials.
| ANLT5050 * |
Concepts of Data Mining
In this course, learners develop their skills in creating a predictive model. Learners apply data mining algorithms, models, and data mining modeling techniques to test, fit, and implement an algorithm and/or model with appropriate tools. Learners practice interpreting results to find an application for those results. Finally, learners apply control, feedback, and evaluation approaches to enhance, continue, or retire the algorithm or model using big data. Prerequisite(s): ANLT5030. Graduate certificate learners in Advanced Analytics Using SAS® are exempt from this prerequisite. |
4 quarter credits |
|---|---|---|
| ANLT5060 * |
Applied Forecasting
In this course, learners evaluate forecast model outcomes to solve organizational problems. Learners examine the impact of time and data latency on forecasting, and practice identifying patterns in the output of forecast models. Learners also apply forecasting techniques in their communication with stakeholders. Prerequisite(s): ANLT5030. |
4 quarter credits |
| ANLT5070 * |
Text Mining
Learners in this course gain an understanding of the early stages of text mining. Learners examine document management practices, text-scraping techniques, and various methods for modeling their findings as they solve text-based mining problems. Prerequisite(s): ANLT5030. Graduate certificate learners in Advanced Analytics Using SAS® are exempt from this prerequisite. |
4 quarter credits |
| ANLT5080 * |
Advanced Analytics and Modeling
Learners in this course demonstrate advanced practice in applying the analytic life cycle. Learners examine approaches to visual analytics and are introduced to geospatial data techniques. Learners also apply their analytic skills to current organizational problems and apply analytic solution scoring and project management skills for effective team performance. Prerequisite(s): ANLT5050. |
4 quarter credits |
| ANLT5100 * |
Visual Analytics
In this course, learners articulate the value of visualization to telling the analytic story to stakeholders. Learners explore the appropriate presentation of types of data and apply best practices for the design of effective visualizations. Learners also develop skills for presenting data to stakeholders in a succinct and relevant manner. Prerequisite(s): ANLT5030. |
4 quarter credits |
*Course has prerequisite(s). See catalog for details.
Learning outcomes
This program will help prepare candidates to assess the information needs for effective strategy and innovation and identify, access, and collaborate on the appropriate sources for that information. On successful completion of this degree and specialization, you will be able to:
- Integrate and apply theory and scholarly research to solve business problems in multiple environments.
- Apply and communicate strategic approaches to business practice and planning.
- Develop and apply critical thinking to business problems and opportunities.
- Integrate internal and external data with analytical techniques to support evidence-based decision-making.
- Integrate ethical concepts and integrity into sustainable business models.
- Develop expertise within and across functional and cross-functional disciplines.
- Apply collaborative techniques to develop relationships, partnerships, and alliances.
The MS in Analytics helps you establish the skills to work with, understand and transform data to support decision-making in global business environments. Students learn how to command analytic tools and develop advanced solutions that address organizational and technical problems. The curriculum is designed to help you analyze business challenges, complete data projects, develop critical systems and applications and adhere to ethical standards.
On successful completion of this program, you should be able to:
- Apply analytic and statistical techniques to support decision-making and problem solving
- Identify data and data sources relevant to a decision-making scenario or problem
- Select analytic tools and statistical methods appropriate to a scenario or problem and justify their usage
- Apply analytic tools, statistical methods, and techniques to address a decision-making scenario or problem
- Address ethical, legal, global and cultural factors in the analytics process at the individual, organizational, and societal levels
- Communicate analytic methods and results with multiple audiences
Review the Capella career exploration guide to learn more about this program and career paths to explore.
Your education can help you reach your professional and personal goals. While Capella cannot guarantee that a graduate will secure any specific career outcome, such as a job title, promotion, or salary increase, we encourage you to explore potential jobs and employment settings. Here are some ideas and examples for a graduate with an MS in Analytics.
Job titles to explore
- Data analyst
- Business analyst
- Director of technology
- Technology manager
- Solutions architect
- Data architect
- Systems analyst
Employment settings to explore
- Land-based or online college or university
- Government – local, state, federal
- Insurance carrier
- Hospital
- Manufacturing
- Financial service
- Consulting service
- Telecommunications carrier
- Bank
- Retail
*These are examples intended to serve as a general guide. Some positions may prefer or even require previous experience, licensure, certifications, and/or other designations along with a degree. Because many factors determine what position an individual may attain, Capella cannot guarantee that a graduate will secure any specific job title, a promotion, salary increase, or other career outcome. We encourage you to research requirements for your job target and career goals.
Capella University is accredited by the Higher Learning Commission.
Accreditation and recognitions provide evidence that we meet standards for quality of faculty, curriculum, learner services, and fiscal stability. See all our accreditations and recognitions.
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