MS in Data Science

2 Years On Campus Masters Program

Fordham University

Program Overview

The Master of Science in Data Science at Fordham University provides students with advanced theoretical and practical knowledge of data analytics, machine learning, artificial intelligence and computational modelling. The STEM-designated, 30-credit program combines technical coursework with hands-on experience using technologies such as Python, Spark, Tableau and deep learning, preparing graduates for careers in data science, financial technology, healthcare analytics and business intelligence.

Curriculum Structure:

Year 1:

Students begin by developing a strong foundation in programming, mathematical modelling, statistical analysis and data management. Courses such as CISC 5450 – Mathematics for Data Science, CISC 5500 – Data Analytics Tools and Scripting and CISC 5790 – Data Mining introduce students to mathematical techniques, programming tools, data exploration and computational methods. Students also develop their understanding of machine learning and algorithms for analyzing complex datasets.

Year 2:

Students advance their expertise through specialized electives, applied machine learning and practical data science projects. Courses such as CISC 5800 – Machine Learning, CISC 5950 – Big Data Computing and CISC 5680 – Generative AI and Foundation Models help students explore predictive modelling, scalable data processing and modern AI applications. Students complete a CISC 6080 – Capstone Project in Data Science, applying their technical knowledge to real-world analytical challenges. Alternatively, they may choose an optional master's thesis or internship in place of the capstone and one elective.

Focus Areas:

Data Science, Artificial Intelligence, Machine Learning, Deep Learning, Generative AI, Statistical Modelling, Data Mining, Big Data Computing, Natural Language Processing, Cloud Computing, Cybersecurity, Bioinformatics, Health Informatics, Computational Finance, Financial Informatics, Urban Informatics, Behavioral Informatics and Data Visualization.

Learning Outcomes:

Graduates will be able to collect, process and analyze large datasets, develop computational and statistical models, apply machine learning and deep learning algorithms, implement scalable data-processing solutions, use programming tools for analytical problem-solving, interpret complex data patterns and communicate findings effectively. They will also develop the ability to apply data science techniques to interdisciplinary challenges in business, finance, healthcare, cybersecurity and scientific research.

Professional Alignment (Accreditation):

The program is offered through Fordham University's Department of Computer and Information Science and emphasizes practical learning through technical coursework, applied projects and industry-relevant technologies. Students can gain experience with Python, Hadoop, Spark, Tableau, NoSQL databases, natural language processing and deep learning. The program is STEM-designated, potentially allowing eligible international graduates to receive up to 36 months of Optional Practical Training (OPT) in the United States. Fordham University is institutionally accredited by the Middle States Commission on Higher Education (MSCHE).

Reputation (Employability Rankings):

650% Growth in Data Science Careers: Fordham highlights the significant expansion of data science career opportunities since 2012, demonstrating the growing demand for analytical and computational expertise.
Leading Alumni Employers: Fordham's MS Data Science alumni have secured opportunities with Amazon, American Express, Ernst & Young, Fidelity Investments, Google, JPMorgan Chase, Mastercard and the U.S. Department of Veterans Affairs.
Google Alumni Success: Junyang Long, an MS Data Science graduate from the Class of 2022, works as a Software Engineer at Google.
Industry-Relevant Skills: Students develop expertise in Python, machine learning, deep learning, big data frameworks and data visualization, supporting opportunities across technology, finance, consulting and healthcare.
Career Opportunities: Graduates can pursue positions such as Data Scientist, Data Engineer, Big Data Engineer, Data Architect, Business Intelligence Analyst, Data Analyst, Data Analytics Manager, Statistician and Information Technology Specialist.

Experiential Learning (Research, Projects, Internships etc.)

At Fordham University, the MS in Data Analytics program is designed to provide students with hands-on experience that translates theoretical knowledge into practical skills. The program emphasizes experiential learning through various opportunities, including collaborative projects, internships, and access to cutting-edge technology and facilities. Students engage in real-world data analysis, working with industry-standard software and tools that prepare them for successful careers in data analytics.

Here are some key aspects of the experiential learning opportunities available in the MS Data Analytics program:

- Collaborative Projects: Students often work in teams on projects that simulate real-world data challenges, fostering teamwork and problem-solving skills.
- Internships: The program encourages internships with leading companies, allowing students to gain valuable industry experience and network with professionals.
- Software and Tools: Students have access to industry-standard software such as R, Python, SQL, and Tableau, equipping them with the skills needed for data manipulation and visualization.
- Research Laboratories: The program utilizes state-of-the-art research labs where students can conduct experiments and analyze data using advanced technologies.
- Field Trips: Students may participate in field trips to local businesses and tech companies, providing insights into how data analytics is applied in various industries.
- Libraries and Resources: Fordham’s libraries offer extensive resources, including databases and journals specific to data analytics, supporting students in their research and projects.
- Institute for Data Analytics: The university hosts the Institute for Data Analytics, which provides additional resources, workshops, and networking opportunities with industry leaders.

Progression & Future Opportunities

The MS in Data Analytics at Fordham University equips graduates with the skills and knowledge to excel in a rapidly growing field. Alumni have successfully secured positions such as Data Analyst, Business Intelligence Analyst, Data Scientist, and Quantitative Analyst. With a strong foundation in data-driven decision-making, graduates are well-prepared to meet the demands of various industries:

- Career Services: Fordham offers dedicated career services, including resume workshops, interview preparation, and networking events tailored specifically for data analytics students.
- Employment Statistics: Over 90% of graduates find employment within six months of graduation, with starting salaries averaging around $80,000, depending on the role and location.
- University–Industry Partnerships: Fordham has established partnerships with leading companies such as IBM and Deloitte, providing students with internship opportunities and real-world projects that enhance their learning experience.
- Accreditation Value: The program is accredited by the Middle States Commission on Higher Education, ensuring that your degree holds long-term value in the job market.
- Graduation Outcomes: Graduates have gone on to work at top firms in finance, healthcare, technology, and consulting, showcasing the versatility of the degree.

Further Academic Progression: After completing the MS in Data Analytics, students have the option to pursue further studies, such as a Ph.D. in Data Science or related fields, or specialized certifications in areas like machine learning or artificial intelligence. This can enhance their expertise and open doors to advanced research roles or leadership positions in the industry.