Master of Science in Data Analytics
The 🌐 icon appears in the title of traditional courses that are also available as a set of module courses.
Description and Outcomes
The Master of Science in Data Analytics program was designed to provide analytics and other domain professionals with advanced-level knowledge in data analytics skills. In this program, you will apply current statistical theories, tools, and processes to curate, manipulate, and present various forms of data. You will master the ability to effectively process data that supports data-informed decisions. You will gain skills across the analytics life cycle, which include data discovery, data aggregation, planning of the data models, data model execution, communication of the results, and operationalization. Whether you intend to apply analytics skills to your current role, undertake a new specialized analytics position, or improve your decision-making by becoming a more analytics-informed leader, this program will help prepare you for those goals.
The program provides you with the option of selecting a concentration, in addition to the core curriculum requirements. You must have sufficient elective credits remaining to be eligible to add a concentration. The concentrations include AWS cloud technologies, blockchain technologies and apps, critical infrastructure security, cybersecurity, enterprise architecture systems, project management, and secure software development and quality assurance.
The Master of Science in Data Analytics program consists of a minimum of 52 quarter credit hours. Upon successful completion of the program, you will be awarded a master of science degree.
- Methods and Tools: Evaluate appropriate methods and tools to be applied to analytics-based challenges and opportunities in a given setting.
- Data Transformation Skills: Transform data sets to provide actionable insights using AI, Machine Learning, statistical and analytics software, e.g., Python, R, SQL, and Tableau.
- Data Analytics Life Cycle: Master the steps in the analytics life cycle from data curation and manipulation through presentation of findings and operationalization.
- Data Infrastructure Skills: Devise infrastructure systems to ensure the quality, security, and privacy of data.
In addition to the discipline-specific outcomes, professional competencies are integrated throughout your academic program. You can review the professional competencies associated with your academic program in the Professional Competencies section of this Catalog.
You must meet the below admissions requirements in addition to Purdue Global's general requirements.
The Dean of the School of Business and Information Technology or a designee will determine if you may enroll.
If you are accepted, you will be provided with an individualized learning plan based on an assessment of your prior learning and/or experience upon enrollment. If you do not have an undergraduate or graduate degree in analytics or a related field, you may be required to complete one or more of the following courses, in the sequence indicated, to fulfill open elective requirements:
- IN555 Statistics for Analytics
- IT527 🌐 Foundations in Data Analytics
- IN500 Survey of Modern Data Analytics
- IN501 Fundamentals of Computer Programming
- IN502 Python Statistical Tools
- IN504 Advanced Applications of Python
Accelerated Master of Science in Data Analytics
If you are a graduate of the University's Bachelor of Science in Analytics, Bachelor of Science in Cloud Computing and Solutions, Bachelor of Science in Cybersecurity, or Bachelor of Science in Information Technology, are granted admission to the Master of Science in Data Analytics, and meet the requirements for the accelerated Master of Science in Data Analytics option, you may have up to three courses waived to matriculate into a shortened program.
In order to qualify for the graduate course waivers, you must meet the following criteria:
- Complete your bachelor’s degree with a minimum cumulative GPA of 3.2.
- Obtain a grade of “B” or above in each of the undergraduate courses required for the graduate course waiver (defined below).
|Waived Graduate Course||Undergraduate Courses Required for Graduate Course Waiver|
|IN500||IN300, IN301, IN302, and MM207|
|IN501||IN300 and IN304; OR IT244 and one course from both of the following groups. Group 1: IT213, IN250, IN251, IN252, IN253. Group 2: IT232, IN254, IN255, IN256, IN257.|
|IN502||IN300, IN301, IN304, MM207|
You may enroll in no more than one course per session for your first three sessions. After completing your third session, you may enroll in two courses per session if your cumulative GPA is 3.5 or higher. Exceptions to this policy require the approval of the Dean of the School of Business and Information Technology or a designee.
Certification, State Board, and National Board Exams
Certain state certification and licensure boards have specific educational requirements for programs to lead to a license or certification that is a precondition for employment in a recognized occupation. Prospective and current students must review Purdue Global’s State Licensure and Certifications site to view program and state-specific licensure information.
Unless otherwise specified, Purdue Global's programs are not designed to meet any specific state’s licensure or certification requirements. Licensure-track programs may limit enrollment to students in certain states; please see Purdue Global’s Program Availability Information to determine enrollment eligibility.
You are responsible for understanding the requirements of optional certification exams. Such requirements may change during the course of your program. You are not automatically certified in any way upon program completion. Although certain programs are designed to prepare you to take various optional certification exams, Purdue Global cannot guarantee you will be eligible to take these exams or become certified. Your eligibility may depend on your work experience, completion of education and/or degree requirements, not having a criminal record, and meeting other certification requirements.