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The 36-credit M.S.A.D.S. curriculum includes an 18-credit Common Core requirement, a 3-to-6-credit analytics application core requirement, 12-15 credits of electives, and a portfolio milestone exit requirement.
Common Core: 18 credits
Class # | Course Title |
IST 659 | Data Administration Concepts & Database Management |
IST 687 | Introduction to Data Science |
IST 707 | Data Analytics |
IST 718 | Big Data Analytics |
MBC 638 | Data Analysis & Decision Making |
SCM 651 | Business Analytics |
Analytics Application Core: 3-6 credits
The Analytics Applications Core provides an opportunity for the student to choose one or two functional area specializations in accounting analytics, financial analytics, marketing analytics, and supply chain analytics, as a way to develop deeper exploration of particular application area(s) for data science techniques.
Class # | Course Title |
ACC 652 | Accounting Analytics |
MAR 653 | Marketing Analytics |
FIN 654 | Financial Analytics |
SCM 702 | Principles of Management Science |
Electives: 12-15 Credits
The Electives include coursework in linear models, time series, scripting for data analysis, natural language processing, information visualization, data warehouse, text mining, information policy, information security and advanced database management. Students should select 4 or 5 courses.
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 Data Administration Concepts & Database Management |
IST 772 | Quantitative Reasoning for Data Science |
Exit Requirement: Portfolio Milestone
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The Common Core includes foundational knowledge in databases, data analysis and business analytics. Students will complete Common Core courses in an order which builds foundational knowledge and skills in preparation for more advanced work. Although not required in the ADS program, fast-track students can also consider a Data Science Internship the summer after their senior year for three credits.
Class # | Course Title | When to Enroll |
IST 659 | Data Administration Concepts & Database Management | FA/SP- Senior Year |
IST 687 | Introduction to Data Science | MYM/SU- after Junior Year |
IST 707 | Data Analytics | FA/SP- Senior Year |
IST 718 | Big Data Analytics | SP/Master’s Year 1 |
MBC 638 | Data Analysis & Decision Making | FA/Master’s Year 1 |
SCM 651 | Business Analytics | FA/Master’s Year 1 |
Disclaimer: Undergraduate coursework for specific graduate equivalent classes in this program must be at a B or better in order to not take the graduate equivalent class. While the equivalent undergrad course with a grade of B or better will fulfill the track requirement, a different graduate-level elective within the field must replace that substituted course/credit. Students can also consider a Data Science Internship the summer after their senior year
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The Analytics Applications Core provides an opportunity for the student to choose one or two functional area specializations in accounting analytics, financial analytics, marketing analytics, and supply chain analytics, as a way to develop deeper exploration of particular application area(s) for data science techniques.
Class # | Course Title |
ACC 652 | Accounting Analytics |
MAR 653 | Marketing Analytics |
FIN 654 | Financial Analytics |
SCM 702 | Principles of Management Science |
Electives: 12-15 Credits
The Electives include coursework in linear models, time series, scripting for data analysis, natural language processing, information visualization, data warehouse, text mining, information policy, information security and advanced database management. Students should select 4 or 5 courses.
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 Data Administration Concepts & Database Management |
IST 772 | Quantitative Reasoning for Data Science |
Exit Requirement: Portfolio Milestone
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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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The Common Core includes foundational knowledge in databases, data analysis and business analytics. Students will complete Common Core courses in an order which builds foundational knowledge and skills in preparation for more advanced work. Although not required in the ADS program, fast-track students can also consider a Data Science Internship the summer after their senior year for three credits.
Class # | Course Title | When to Enroll |
IST 659 | Data Administration Concepts & Database Management | FA/SP- Senior Year |
IST 687 | Introduction to Data Science | MYM/SU- after Jr. Year |
IST 707 | Data Analytics | FA/SP- Senior Year |
IST 718 | Big Data Analytics | Spring/Masters Year 1 |
MBC 638 | Data Analysis & Decision Making | Fall/Masters Year 1 |
SCM 651 | Business Analytics | Fall/Masters Year 1 |
Disclaimer:Undergraduate coursework for specific graduate equivalent classes in this program must be at a B or better in order to not take the graduate equivalent class. While the equivalent undergrad course with a grade of B or better will fulfill the track requirement, a different graduate-level elective within the field must replace that substituted course/credit. Students can also consider a Data Science Internship the summer after their senior year
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The Analytics Applications Core provides an opportunity for the student to choose one or two functional area specializations in accounting analytics, financial analytics, marketing analytics, and supply chain analytics, as a way to develop deeper exploration of particular application area(s) for data science techniques.
Class # | Course Title |
ACC 652 | Accounting Analytics |
MAR 653 | Marketing Analytics |
FIN 654 | Financial Analytics |
SCM 702 | Principles of Management Science |
Electives: 12-15 Credits
The Electives include coursework in linear models, time series, scripting for data analysis, natural language processing, information visualization, data warehouse, text mining, information policy, information security and advanced database management. Students should select 4 or 5 courses.
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 Data Administration Concepts & Database Management |
IST 772 | Quantitative Reasoning for Data Science |
Exit Requirement: Portfolio Milestone
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Two Courses per Term/Semester
*=Common Core Class
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) |
Three Courses per Term/Semester
Term/Semester | Course 1 | Course 2 | Course 3 |
1 | MBC 638 – Data Analysis & Decision Making* | IST 659 – Data Admin Concepts & Database Mgmt* | IST 687- Introduction to Data Science* |
2 | SCM 651 – Business Analytics* | IST 707- Data Analytics* | IST 664 – Natural Language Processing (example elective) |
3 | FIN 654- Financial Analytics OR different Analytics Application Core Course | IST 719 – Information Visualization (example elective) | IST 736 – Text Mining (example elective) |
4 | MAS 777 - Times Series Modeling and Analysis (example elective) | IST 718 – Big Data Analytics* | IST 722 – Data Warehouse (example elective) |
Four Courses per Term/Semester
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) |
Required and Recommended Pre-Requisites for M.S.A.D.S.
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Programming Languages in M.S.A.D.S Common Core
Course | Machine Learning | Python | SQL | R | Big Data | DB Mgmt | Statistics | Visualization | Google Analytics | Tableau | MS Power BI |
IST 659: Data Admin Concept & Mgmt |
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| X SQL Servicer, Access, Visio |
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| X |
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IST 687: Intro to Data Science | X |
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| X R/R Studio |
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| X | X |
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IST 707: Data Analytics | X |
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| X R/R Studio: arules, Rweka, class e1021, caret |
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| X | X |
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IST 718: Big Data Analytics | X | X Apache Spark, Hadoop 2.0, Spark ML, Pandas, Matplotlib |
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| X |
| X |
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MBC 638: Data Analysis & Decision Making |
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| X |
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SCM 651: Business Analytics | X Neural Networks, K-means clustering, decision trees |
| X | X |
| X | X Linear and non-linear regression, logit, probit, ordered logit, multinomial logit, conjoint analysis | X | X Analytics & AD Words | X Analysis & dashboard | X Analysis & dashboard |
Programming Languages in M.S.A.D.S. Analytics Application Core
Course | R | Statistics | Visualization |
ACC 652: Accounting Analytics |
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MAR 653: Marketing Analytics |
| X |
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FIN 654: Financial Analytics | X | X |
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SCM 702: Principles of Mgmt Science |
| X | X |
Programming Languages in M.S.A.D.S. Electives
Course | Machine Learning | Python | SQL | NoSQL | R | Big Data | DB Mgmt | Statistics | Visualization |
IST 652: Scripting for Data Analysis |
| X |
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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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| X |
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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| X | X |
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IST 736: Text Mining | X | X Panda, Scikit Learn |
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IST 769: Advanced Data Admin Concepts & Mgmt |
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| X | X |
| X | X |
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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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| X | X |
Differences between M.S. Applied Data Science and M.S. Business Analytics
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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 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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- 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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Below is just one example of how a full-time campus-based student would complete a C.A.S. in information security management, concurrently with the M.S.A.D.S. degree. Students will need to take two additional courses to complete this C.A.S. To view the requirements of the C.A.S, please refer to the appropriate advising check sheet, which can be found in 114 Hinds Hall, Student Services, or ischool.syr.edu/academics/advising/handbooks-checksheets/.
Fall 2019
Class # | Course Title | Credits | Notes |
IST 659 | Data Admin Concepts & Database Mgmt | 3 | MS Common Core and CAS elective |
IST 687 | Introduction to Data Science | 3 | MS Common Core |
MBC 638 | Data Analysis and Decision Making | 3 | MS Common Core |
Spring 2020
Class # | Course Title | Credits | Notes |
IST 623 | Introduction to Information Security | 3 | MS elective and CAS Primary Core |
IST 652 | Scripting for Data Analysis | 3 | MS example elective |
IST 707 | Data Analytics | 3 | MS Common Core |
SCM 651 | Business Analytics | 3 | MS Common Core |
Summer 2020
Class # | Course Title | Credits | Notes |
IST 625 | Enterprise Risk Management | 3 | CAS Secondary Core example |
Fall 2020
Class # | Course Title | Credits | Notes |
IST 618 | Information Policy | 3 | MS elective and CAS elective |
IST 719 | Information Visualization | 3 | MS example elective |
MAR 653 | Marketing Analytics | 3 | MS Analytics Application Core example |
Spring 2021
Class # | Course Title | Credits | Notes |
IST 636 | Leading Issues in Information Security | 3 | CAS Secondary Core example |
IST 718 | Big Data Analytics | 3 | MS Common Core |
IST 722 | Data Warehouse | 3 | MS example elective |
| Portfolio Milestone Requirement |
| Exit Requirement |
Focus Areas at the iSchool
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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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Depending if you are in the 36-credit program, Fast Track, or Executive-Status, your requirements are different. You can find your requirements on the advising check sheets located at ischool.syr.edu/academics/advising/handbooks-checksheets/. More information can be found on pages 6-12 of this handbook.
I need advising help with my courses. Who do I speak to?
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While there is no such thing as a “dual” degree at the graduate level, students can enroll in two master’s degrees concurrently. You should contact your program manager or academic advisor for information on how to apply. More information can be found on page 24 and 28 of this handbook.
When and how can I apply for a C.A.S?
Students are strongly encouraged to add their chosen C.A.S. in their first year of graduate study. The final deadline for students to add a C.A.S. is the financial deadline to drop a class of their final semester of study. Visit the academic calendar to view the financial deadline to drop a class at syracuse.edu/academics/calendars. For information on how to apply, please contact your program manager or academic advisor. More information can be found on pages 15 and 28 of this handbook.
What kinds of financial aid are available? How and when do I apply?
Merit scholarships are available for the on-campus program only. At the graduate school level, financial aid is merit-based, not need-based. Students have the opportunity to apply each semester and should contact their program manager on how to apply. More information can be found on page 29 of this handbook.
How do I transfer credits, and how many can I transfer in?
Master’s students, if eligible, may transfer a maximum of six hours of graduate credit into the M.S.A.D.S program. Coursework must be directly relevant to the degree program, have been taken within seven years of the date the student will receive the degree, must be graduate-level work, and must show a grade of B or better. Coursework coming from outside of Syracuse University requires an official transcript. More information can be found on pages 26 of this handbook.
How do I reduce credits from my degree?
Many students wish to reduce the 36-credit course load due to full-time work experience. More information on credit reductions and substitutions can be found on your program’s advising check sheet, as well as page 7-8 of this handbook.
I need help finding an internship. Who do I talk to?
An internship is not a requirement of the M.S.A.D.S. program, however, students may elect to pursue one in substitution of a program elective. Students should note that internships are highly competitive and the iSchool cannot guarantee a paid internship arrangement. More information can be found on page 32 of this handbook.
How do I waitlist for a class?
If a class you want to register for is full or set to Department Consent, you will need to waitlist for the course, which can be done through my.ischool.syr.edu. The iSchool’s advising staff manages and prioritizes the waitlist and will provide permission to students if they are eligible and seats are available. Campus students should email iAdvising@syr.edu for instructions on how to waitlist, and online students should email their student success advisor.
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iSchool students need to complete two major steps in order to graduate and have their degree certified. First, you need to file a Diploma Request on MySlice. Second, you need to fill out a Program of Study Form. Campus students can submit this form to iAdvising@syr.edu. Online students can submit this form to their online student success advisor. More information can be found on page 26 of this handbook.
What happens if I take a semester off from school?
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