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Strengthen your foundational knowledge with a Master of Science in Information Technology, Analytics. Gain vital skills in data-driven decision-making, statistical methods, and cultural and ethical aspects of data analysis. Engage in problem solving with hands-on coursework and develop best practices that help you grow as an individual contributor. Expand your career possibilities with a deeper knowledge of developing technology solutions and how they apply to a globally diverse field.
Use the code SPRING to waive the $50 application fee.
Enroll in a qualified program and apply for a $2.5K Capella Progress Reward, a scholarship to help fund your master’s degree. Eligibility rules and exclusions apply. Connect with us for details.
Foundations in Analytics
Learners in this course apply data management fundamentals to data models. Learners examine the concepts of data mining, ETLs, and data warehouses and also evaluate applied analytics in professional domains such as finance, marketing, and health care. Prerequisite(s): Completion of or concurrent registration in ANLT5002 or HMSV5002 or PM5018 and ITEC5020.
|4 quarter credits|
Data Sources for Analytics
In this course, learners explain database methodologies including relational databases, flat files, dimensional modeling, RSS feeds, and multi-dimensional modeling. Learners examine the impact of data quality on analytics and apply ETL techniques and processes. Finally, learners evaluate the application of data warehouses, data marts, and multi-dimensional cubes to decision-making and action. Prerequisite(s): Completion of or concurrent registration in ANLT5010.
|4 quarter credits|
Statistical Methods in Analytics
In this course, learners study the collection, organization, presentation, analysis, and interpretation of data using statistical methods. Learners practice using appropriate tools to obtain a result using statistical methods and collaborate with team members to compare processes, techniques, and conclusions to understand various perspectives. Prerequisite(s): Completion of or concurrent registration in ANLT5020.
|4 quarter credits|
Predictive Models and Classification Methods
Learners gain the skills to utilize historical data to predict future outcomes, as well as identify patterns in current data that can be used to classify or group future observations. Learners complete their own analytics project through hands-on statistical techniques coupled with a broad understanding of contemporary predictive modeling and analytics classification methods. Prerequisite(s): ANLT5030.
|4 quarter credits|
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.
This specialization develops your ability to understand, apply, and transform data to support analytical decisions. You’ll acquire the skills and knowledge to address applied organizational and technical problems in a diverse global environment, including the ability to design and evaluate IT systems and applications. An advanced understanding of analytics tools will anchor your ability to analyze business problems, complete data projects, and adhere to ethical standards.
On successful completion of this program, you should be able to:
Review the Capella career exploration guide to learn more about this program and career paths to explore.
Program eligible for Workplace Integrated Learning
Use your experience: bring your real-world projects into the courseroom to complete assignments and apply what you’ve learned in your field.
The total cost of your degree will depend on academic performance, transfer credits, scholarships and other factors. See GuidedPath cost information below.
A structured learning format with an active peer community and faculty guidance. We’ll set the schedule, you meet the deadlines.
$715 per credit, 48 total quarter credits, 12 max transfer credits
*This is only an estimate, effective July 10, 2023, and is subject to change. Your price will vary depending on your specialization, transfer credits, and tuition discounts. Books, supplies, and other fees are not included in this estimate. GuidedPath prices show the tuition you would pay if you brought in an average number of transfer credits or the maximum allowed transfer credits. New or recently revised program estimates are based on comparable programs.
Capella is committed to transparency in its tuition and pricing. In addition to tuition, you will be responsible for additional costs, which may include an application fee, travel expenses, and practicum costs. A resource kit fee of $50-$175, charged quarterly or per billing session, covers the cost of required books, software, and other course materials. Click here to review program-specific fee amounts in our University Catalog.
Find out more about financing and payment options to help you complete your program. Federal aid also is available to help manage the costs of higher education. Learn more about financing your education.
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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.
Applicants to the MSIT in Analytics program must provide the following information for admission:
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:
Learn more about international student admissions.
Our programs are designed to meet the unique needs of a master’s student. We’ve structured the experience in manageable pieces to help you earn your degree with support from faculty, staff and online resources.
Expand your perspective on academic and career topics with articles and resources from Capella University.
Pursuing a degree in Information Technology (IT) or Computer Science may be a good idea for your future career.
Hands-on experience helps us think critically and learn quickly. Encounters with previous problems, especially in IT, are often the best predictor of our ability to solve a new one.
These books address the implications of new technologies, convey lessons in leadership and ethics, and provide in-depth topical knowledge and insights from the IT world.
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 MSIT in Analytics.
*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.