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The 36-credit Fast Track is an accelerated degree program for the MS in Applied Data Science (MSADS), and students to complete as many as nine (9) graduate credits by the time their undergraduate degree is conferred. Fast Track also gives students the option to enter the workforce after graduation and complete the remainder of the program online and/or part-time.
Eligibility, Application Deadlines, and Fast-Track Timeline
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Class # | Course Title |
MAS 766 | Linear Statistical Models |
MAS 777 | Time Series Modeling Analysis |
IST 615 | Cloud Management |
IST 618 | Information Policy |
IST 623 | Introduction to Information Security |
IST 652 | Scripting for Data Analysis |
IST 664 | Natural Language Processing |
IST 719 | Information Visualization |
IST 722 | Data Warehouse |
IST 736 | Text Mining |
IST 769 | Advanced Big Data Administration Concepts & Database Management |
IST 772 | Quantitative Reasoning for Data Science |
IST 974 | Internship in Applied Data Science |
Exit Requirement: Portfolio Milestone
Students In their final term or semester, students are required to complete a portfolio milestone to provide an assessment of learning for their program. Students will choose assignments and projects worked on in courses during the course of study, which reflect abilities specified in the program learning outcomes for inclusion in their personal portfolio. A panel of faculty Students will be given access to a course shell where they can find the details of the portfolio milestone. A faculty member who teach the courses included in the program will review the portfolios of graduates during the student’s final term . The panel or semester, and will approve the portfolio for each student as a transcript milestone required for the degree.
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Term/Semester | Course 1 | Course 2 |
1 | MBC 638 – Data Analysis & Decision Making* | IST 659 – Data Administration Concepts & Database Mgmt* |
2 | SCM 651 – Business Analytics* | IST 687 – Introduction to Data Science* |
3 | IST 707 – Data Analytics* | IST 652 – Scripting for Data Analysis (example elective) |
4 | MAR 653 – Marketing Analytics OR different Analytics Application Core Course | IST 719 – Information Visualization (example elective) |
5 | MAS 777- Times Series Modeling and Analysis (example elective) | IST 736 – Text Mining (example elective) |
6 | IST 718 – Big Data Analytics* | IST 722 – Data Warehouse (example elective) |
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Term/ Sem | Course 1 | Course 2 | Course 3 | Course 4 |
1 | MBC 638 – Data Analysis & Decision Making * | IST 659 – Data Admin Concepts & Database Mgmt* | IST 687- Introduction to Data Science* | SCM 651 – Business Analytics* |
2 | IST 707- Data Analytics* | IST 719- Information Visualization (example elective) | IST 652 – Scripting for Data Analysis (example elective) | SCM 702- Principles of Management Science OR different Analytics Application Core Course |
3 | MAS 777- Times Series Modeling and Analysis (example elective) | IST 718 – Big Data Analytics* | IST 769 – Advanced Data Admin Concepts and Database Mgmt (example elective) | IST 736 – Text Mining (example elective) |
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- IST 652 is a recommended pre-requisite for IST 707
- IST 652 is a recommended pre-requisite for IST 718
- IST 652 is a recommended pre-requisite for IST 736
- IST 659 is a recommended pre-requisite for IST 652
- IST 659 is a required pre-requisite for IST 722
- IST 659 is a required pre-requisite for IST 769
- IST 664 is a recommended pre-requisite for IST 736
- IST 687 is a required pre-requisite for IST 707
- IST 687 is a required pre-requisite for IST 718
- IST 687 is a required pre-requisite for IST 719
- IST 687 is a required pre-requisite for IST 736
- MBC 638 and SCM 651 are recommended pre-requisites for FIN 654
- MBC 617 OR MBC 635 and MBC 638 are required pre-requisites for SCM 702
- MBC 638 is a required pre-requisite for MAS 777
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Course | Machine Learning | Python | SQL | NoSQL | R | Big Data | DB Mgmt | Statistics | Visualization |
IST 652: Scripting for Data Analysis |
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IST 664: Natural Language Processing | X | X NLTK |
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IST 719: Info Visualization |
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| X plotrix, igraph, maps, rworldmaps, ggplot2, lubridate, worldclous2, RColorBrewer, png, rgl |
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IST 722: Data Warehouse |
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| X Microsoft Stack of BI Tools: SQL Server/ROLAP, MDBMS/MOLAP, ETL, Portals, KPIs |
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IST 736: Text Mining | X | X Panda, Scikit Learn |
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IST 769: Advanced Big Data Admin Concepts & Mgmt |
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IST 772: Quant Reasoning for Data Science |
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| X (R/R Studio: includes packages for Bayesian methods, ANOVA, Regression, Time Series |
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The choice between Business Analytics and Applied Data Science ultimately comes down to a student’s post-graduation career goals. Data scientists have been ranked as Glassdoor’s No. 1 best job of from 2016-2019, and they are critical to the success of any organization. As the data science field evolves, the demand for analytics skills continues to grow. Employers are actively seeking candidates with the advanced technical expertise to make data-driven decisions. Many Data Science graduates pursue jobs in the engineering and IT field and more technical roles that manage large amounts of data, create visualizations, and design and deploy algorithms that support decision-making tools. Business Analytics students desire greater business experience and specialized knowledge to lead their team or organization. They may work as business analysts or analytics managers, or they may need analytics knowledge to advance in marketing or accounting teams. In these roles, professionals extract data to explain trends, predict future performance, determine best approaches, and explain solutions to stakeholders.
Courses and Curriculum
Both programs are STEM designated and 36-credit hours.
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One difference between our campus and our online M.S.A.D.S. is the course schedule which differs from the typical University semester schedule. Traditional SU semesters run three times per year for 15 weeks: one in the fall, which begins in August, one in the summer, which begins in May, and one in the spring, which begins in January. Courses offered in our online M.S.A.D.S, run four times per year, or in quarter terms, for 11 weeks. SU has a separate academic calendar, a quarter-term calendar, which provides dates and deadlines specifically for our online students. This academic calendar lists registration dates, financial deadlines, first day of asynchronous coursework, first day of live face-to-face classes, final examination dates, grade availability, etc. The 20192020-2020 2021 quarter term calendar can be found at syracuse.edu/academics/calendars/quarter-term/.
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- IST 649 M001 3 credits
- IST 719 M401 3 credits
- IST 722 M400 3 credits
Certificates of Advanced Study (C.A.S.)
The Certificates of Advanced Study at the iSchool are 15-credit graduate-level certificates that can be taken as stand-alone certificates or as part of a graduate degree program. With a little planning, students can receive both the M.S.A.D.S. and a C.A.S. from the iSchool with only two additional courses to complete the C.A.S. Students who consider an iSchool C.A.S. want to study the latest in information field trends, learn about emerging technologies, boost their workplace edge, freshen their resume, and keep current with changes in the profession.
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- No scholarships awarded to students by another school will transfer into the iSchool
- International students with a non-STEM visa who are coming into a STEM program, and international students who are transferring into a program with a higher or lower number of credits needed to graduate, must notify the Slutzker Center so that they can report the facts of their present situation to immigration services for potential visa adjustment
- Students may transfer a maximum of 6 credits of elective courses into the M.S.A.D.S. program from outside of the iSchool or Syracuse University. Students who want to transfer in courses from other Universities are required to submit a Petition to Transfer Credits form. This will meet the six-credit transfer policy of the program and no more non-IST classes would be allowed. Students who want to transfer in courses from outside of the iSchool but within SU are required to submit a Petition to Faculty form. All classes being transferred in, whether from SU or outside of SU require a minimum grade of B, the course completed should be graduate level, and credits must have been earned within seven years of when the student graduates from the iSchool. Petition forms can be found here: ischool.syr.edu/academics/advising/advising-forms/.
Graduate Degree and Graduation Requirements
Applying for Graduation
Please review the website for graduation requirements here: ischool.syr.edu/academics/advising/graduation-requirements/
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The mission of the Center for Emerging Network Technologies, or CENT, is to understand the future of networking technologies, and to engage students, faculty and industry in the process of defining and shaping that future. Convergence refers to the power of digital media to provide unified communications and new applications, devices and networks involving voice, video, data, text and money. Emerging Network Technologies refers to the other economic and technological trends affecting networking, such as new architectures and protocols and new forms of wireless broadband access. The Center’s research is interdisciplinary and applied, focusing on the management and use of networks and communication as well as relevant public policy and industrial organization issues. The Center serves three distinct constituencies: 1.) It provides a platform for faculty research on digital convergence and networking, 2.) It provides experiential learning for graduate and advanced undergraduate student teams, and 3.) It serves as a mutually beneficial learning interface between the networking technology industries and the School of Information Studies. For more information on projects in CENT, visit ischool.syr.edu/research/research-centers/center-for-emerging-network-technologies/
iConsult Collaborative
The iConsult Collaborative is a university-wide program to build experience for students through real-world client projects involving digital transformation. Student participants in iConsult form project teams representing needed specialty domains of the schools and colleges of the University. Each iConsult team works under the direction of faculty mentors and a student Project Leader who oversees the client relationship and the team’s deliverables. iConsult Project teams analyze, design, recommend, and apply known information tools and approaches to help clients integrate digital technology into their organizations. In 2018, iConsult was revised and expanded into a University-wide program in collaboration with both corporate and community engagement partners and sponsors. This gives the opportunity to involve students from multiple schools and colleges within the University in cross-functional teams. The iConsult Collaborative, as it is now known, builds upon its long-term foundation to work on a broad range of projects leading toward the digital transformation of its clients in several business sectors. The iSchool directs and manages the iConsult Collaborative on behalf of the University. For more information, visit ischool.syr.edu/careers/careerkickoff/iconsult/.
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