Master of Science in Applied Data Science
Syracuse, USA
MSc
DURATION
2 years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
01 Jun 2026*
EARLIEST START DATE
Aug 2026
TUITION FEES
USD 62,007 / per year **
STUDY FORMAT
Distance Learning, On-Campus
* Priority Date 1: October 1 | Priority Date 2: November 15 | Deadline: December 15
** 2025-26 specifically for students entering the on-campus program total: International applicants need to show this amount on their financials
Key Summary
Use data to gain insight and solve problems in the real world.
We’re living in an age where data powers our daily lives, and organizations of all forms and sizes are using data to drive critical decision-making processes.
Gathering this data raises questions about accuracy, privacy, equality, and ethics. Analyzing it requires deep analytical and technical expertise. And using it to inform decisions requires communication and management skills.
These skills have never been in higher demand. In fact, Glassdoor has ranked data scientist as the best job for the last five years in a row. Our program prepares you for this rewarding career and is designed for students looking to gain data analytics expertise, whether you already have a background in technology or are starting a new career path.
As the data science field has grown, specialties within the subject field continue to emerge and grow. That’s why we’ve designed seven concentrations to allow you to pursue deeper study in a particular aspect of the field. Students can choose from the following conecnertations within the Applied Data Science program: Artificial Intelligence, Big Data, Data & Business Analytics, Data Pipelines & Platforms, Language Analytics, Project Management, and Visual Analytics.
No matter which concentration you choose, you’ll graduate with the data science skills needed to make an impact on any industry. The program may be completed in one calendar year through summer and Winterlude coursework, depending on course availability.
A vibrant learning community.
Connect with leaders in the data science field, forge friendships and connections with peers in your industry, and gain a lifelong network. Life here is active in and outside of the classroom.
Delve deeper, explore farther.
In addition to getting practical, on-the-job experience, you’ll have opportunities to join a research lab or collaborate with faculty on their academic work. Your focus on data science will mean your skills will be in demand on almost any iSchool research team.
The same faculty and coursework, available online.
As leaders in technology, we’ve been teaching online for decades. Our online program combines live weekly classes, multimedia coursework, and collaborative group learning exercises with a platform to help you cultivate lifelong professional relationships with professors and alumni worldwide.
You’ll learn from the same faculty and take the same courses as the on-campus program, and enjoy the same access to the Orange network when you graduate.
Courses & Curriculum
The Applied Data Science (ADS) program is 34 credits and may be completed in one calendar year through summer and Winterlude coursework, depending on course availability. The curriculum combines a primary core, secondary core (your data science concentration), and electives to give you a strong data science foundation with a focus of your choosing.
The 34 credits are distributed as follows:
- Required Core – 15 credits
- Secondary Core – 6 credits from one concentration
- Choose between 7 concentrations: Artificial Intelligence, Big Data, Data & Business Analytics, Data Pipelines & Platforms, Language Analytics, Project Management, and Visual Analytics.
- Elective Courses – 12 credits
- Choose any course from an additional track for 3 credits or an additional course from their own track for 3 credits.
- Exit Requirement – 1 credit
- Complete a required one-credit course in which you submit a personal portfolio of projects that demonstrate full competency of the learning outcomes to a panel of program faculty.
Program Requirements
Primary Core: 15 credits
The 15-credit primary core includes foundational knowledge in databases, data analysis and business analytics. Students will complete courses in an order which builds foundational knowledge and skills in preparation for more advanced work.
- IST 659 - Data Administration Concepts and Database Management - 3 credits
- IST 686 - Quantitative Reasoning for Data Science - 3 credits
- IST 687 - Introduction to Data Science - 3 credits
- IST 707 - Applied Machine Learning - 3 credits
- SCM 651 - Business Analytics - 3 credits
Secondary Core: 6 credits
Students select 2 courses (6 credits) from one of the concentrations below.
AI
- IST 664 - Natural Language Processing - 3 credits
- IST 691 - Deep Learning in Practice - 3 credits
- IST 692 - Responsible AI - 3 credits
Big Data
- IST 718 - Big Data Analytics - 3 credits
- IST 769 - Advanced Big Data Management - 3 credits
Data and Business Analytics
- ACC 652 - Accounting Analytics - 3 credits
- FIN 654 - Financial Analytics - 3 credits
- MAR 653 - Marketing Analytics - 3 credits
- MBC 638 - Data Analysis and Decision Making - 3 credits
- SCM 703 - Principles of Management Science - 3 credits
Data Pipelines and Platforms
- IST 652 - Scripting for Data Analysis - 3 credits
- IST 722 - Data Warehouse - 3 credits
- IST 769 - Advanced Big Data Management - 3 credits
Language Analytics
- IST 664 - Natural Language Processing - 3 credits
- IST 736 - Text Mining - 3 credits
Project Management
- IST 644 - Managing Data Science Projects - 3 credits
- IST 692 - Responsible AI - 3 credits
Visual Analytics
- IST 719 - Information Visualization - 3 credits
- IST 737 - Visual Analytic Dashboards - 3 credits
Electives: 12 credits
Students can also choose any course from a different track for three credits, an additional course in the chosen track if available, or any course from the list below.
- IST 615 - Cloud Management - 3 credits
- IST 618 - Information Policy - 3 credits
- IST 623 - Introduction to Information Security - 3 credits
- IST 644 - Managing Data Science Projects - 3 credits
- IST 974 - Internship in Applied Data Science - 3 credits
- MAS 766 - Linear Statistical Models I: Regression Models - 3 credits
- MAS 777 - Time Series Modeling and Analysis - 3 credits
Exit Requirement: 1 credit
Students take IST 782 in their last semester of study.
- IST 782 - Applied Data Science Portfolio - 1 credit
Total Credits Required: 34
Transfer Credits
6 credits in related coursework can be transferred from other universities with the approval of the Program Director.
Part-Time Study
U.S. citizens, and non-citizens with the appropriate visa and/or immigration permissions for part-time study, may pursue this program on a part-time basis.
Satisfactory Progress
Students are required to have a 3.0 grade point average or higher to maintain satisfactory progress.
Notes
On-campus courses are delivered through the traditional semester format in which students take courses in the fall and spring semesters, with optional internships in the summer. Section sizes for on-campus classes range from 20-35 students. Online courses are delivered with four (4) starts per year, where courses run for 11 weeks with required contact hours achieved through a mix of asynchronous and synchronous course interaction.
Learning Outcomes
As an interdisciplinary program, the master’s in Applied Data Science provides students the opportunity to learn in a broad range of areas related to data science. Successful students in our program will be able to:
- Collect, store, and access data by identifying and leveraging applicable technologies.
- Create actionable insight across a range of contexts (e.g., societal, business, political), using data and the full data science life cycle.
- Apply visualization and predictive models to help generate actionable insight.
- Use programming languages such as R and Python to support the generation of actionable insight.
- Communicate insights gained via visualization and analytics to a broad range of audiences (including project sponsors and technical team leads.
- Apply ethics in the development, use, and evaluation of data and predictive models (e.g., fairness, bias, transparency, privacy).
What can I do with a master’s in applied data science?
This advanced degree equips you with the skills necessary to work in various industries, including technology, healthcare, finance, marketing, and more. With the growing demand for data-driven decision-making, there are numerous career possibilities available for those with a strong background in data science.
Sample Job Titles
- Data Scientist
- Data Analyst
- Machine Learning Engineer
- Business Intelligence Analyst
- Data Engineer
- Statistical Analyst
- Artificial Intelligence Specialist
- Data Consultant
- Quantitative Analyst (Quant)
- Research Scientist
Careers
Gain in-demand skills that make you highly sought after by employers across industries. Here, you’ll gain the experience and support you need to launch and grow your career.
Career Outlook
Gain deep industry experience, and graduate prepared and ready to contribute on day one. Enter a field that boasts some of the highest salaries, largest growth potential, and best job satisfaction rates.
Students in a group take a moment to listen to their peers
Focus on Experience
Work with industry leaders. Consult with clients. Network with top employers. Work at highly sought-after internships. Here, getting hands-on experience is part of the everyday, in and out of the classroom.
Services & Support
We help you find the career that fits your passions. From connecting you with employers to helping with your resume and interview skills and negotiating your offer, you’ll have the support you need.
Corporate Partnerships
Work with us to hire the best candidates, grow your talent pipeline, and gain the analytical and data-driven expertise you need to drive business growth.
Staff
Our team of experts will support you from your time on campus throughout your professional career to help you reach your goals.