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Graduate Programs for Working Professionals

Masters of Science in Information Technology and Web Sciences:
Data Science & Analytics

Rensselaer Polytechnic Institute’s Information Technology and Web Science program concentrates in Data Science & Analytics, preparing professionals to effectively use advanced analytic and/or web-based tools and languages to answer questions and solve problems using latest techniques and tools in the industry. The program is built specifically to meet the needs of today’s professional seeking new professional challenges.

The program prepares professionals to analyze large and complex structured and unstructured data sets and formulate appropriate data-supported answers to critical questions. The program prepares professionals to interact with data systems and data science environments; construct testable and contextualized hypotheses; build, gather and evaluate data sets; formulate data queries; perform appropriate significance tests; interpret results; and, present and explain results and their implications for the organization.

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Degree Information

  • The program results in a Master of Science in Information Technology and Web Sciences degree.
  • The Program is delivered using online and blended instruction designed to fit into the lives of busy professionals.
  • In the Capstone Project, students work with faculty members to design and implement individual applied projects that demonstrate program mastery.
  • See our website for starting dates and application guidelines.

Curriculum

Courses

Credits

ITWS 6350

Data Science

3

ITWS 6300

Business Issues

3

ITWS 6600

Data Analytics

3

ITWS 6700

Software Development

3

ITWS 6400

X-Informatics

3

CSCI 4380

Database Systems

3

COMM 6420

Foundations of HCI Usability

3

ISYE 6180

Knowledge Discovery with Data Mining

3

CSCI 4440

Software Design & Documentation

3

ITWS 6800

Capstone Project

3

Total Credit Hours

30

Course Coverage:

Data Science: Data science is advancing the inductive conduct of science and is driven by the greater volumes, complexity and heterogeneity of data. It combines aspects of data management, library science, computer science, and physical science. It is changing the way these disciplines do both their individual and collaborative work. Key methodologies in application areas based on real research experience are taught.

Business Issues: This course develops frameworks for asking the appropriate questions and framing the organization’s issues in ways such that data can be objectively employed and answers found. The course looks at issues being faced by organizations today to develop modeling rules and standards. Issues such as client need, organizational efficiency, degree of competitiveness, and validation of metrics are analyzed.

Data Analytics: The world at-large is confronted with increasingly larger and more complex sets of structured/unstructured information. Data and information analytics extends analysis (descriptive models of data) by using data mining and machine learning methods, with optimization and validation, to recommend action or guide and communicate decision-making.

Software Development: This course teaches students about the roles and infrastructure of IT departments in modern organizations, IT software engineering technologies and methodologies for software development life cycles through hands-on experience. The course is for students with software development background to enhance their knowledge of software development and management.

X-Informatics: Informatics covers a broad range of disciplines addressing challenges in the explosion of data and information resources. X-informatics provides commonality for implementations in specific disciplines. The theoretical bases of informatics are information and computer science, cognitive science, social science, library science; this course adds the practice of information processing, and the engineering of information systems.

Database Systems: Students master modern database systems, with an emphasis on relational systems. Topics include database design, database system architecture, SQL, normalization techniques, storage structures, query processing, concurrency control, recovery, security, and new directions such as object-oriented and distributed database systems.

Foundations of HCI Usability: This course builds methods for gathering users’ requirements for product functions and information, ways to test products and information for usability and suitability, and procedures for incorporating the results learned through testing.

Database Mining: This course takes a multi-disciplinary approach to data mining and knowledge discovery involving statistics, rule and tree induction, neural networks, genetic algorithms, visualization and fuzzy logic. The course is project driven and puts a special emphasis on the use of computational intelligence for scientific data mining related to drug design and bioinformatics./p>

Software Design and Documentation: Software system design methodology emphasizing use of object oriented modeling and software systems, and emphasizing written and oral communication in software engineering. Project management and software testing. Individual and team projects include specification, software architecture, user interfaces, and documentation of the phases of a project.

Capstone: The course utilizes a Team Project with a real organization to practice major IT concepts. Team members select, develop, and present a significant technology implementation project, incorporating strategy, systems development, and business planning.

Accelerated Application Process

A dedicated admissions officer will guide you through the process from start to finish as you prepare and submit all of the required application components.
An admissions decision will be made within 2 weeks of application submission.

Accelerated Application Requirements:

Application Component

Completed By Applicant

Requested By Applicant

Online Application

X

Official Transcripts

X

Resume

X

Standardized Test Scores (GRE* or RSI**)

X

X

Two letters of recommendation***

X

Statement of Goals

X

*Graduate Record Examination (GRE): The GRE is recommended for applicants with fewer than 3 years of professional experience. The GRE test is administered by the Educational Testing Service (ETS). A Rensselaer admissions representative can help you find a testing center available in their region.

**Rensselaer Success Indicator (RSI): For those with 3+ years of professional experience, the RSI evaluates non-cognitive skills and personal attributes as demonstrated throughout an individual’s professional career. Applicants request an online evaluation from five individuals familiar with their academic and/or professional performance.

***Recommendation Letters: Individuals who apply using the RSI are not required to submit letters of recommendation.

Informational Webinars

Attend a free webinar with our Graduate Program Director to learn how Mechanical Engineering students benefit from our blended learning approach and application of cutting edge research to the classroom. Instructions on how to apply will be covered and participants will receive a $75 application fee waiver for attending.

Informational Webinar Schedule

Get More Information

Complete Our Inquiry Form: https://apply.rpi.edu/register/APSinquiry
Visit Our Program Website: https://admissions.rpi.edu/graduate/admission/aps.html
For More Information contact Natalie Sutera, sutern@rpi.edu 860-548-2412

Questions?


Updated: 2017-10-18, 10:08