Data Science
The Master of Science in Data Science provides a comprehensive and computationally rigorous curriculum designed for students who want to develop deep expertise in analyzing, interpreting, and modeling large-scale datasets. The program integrates coursework in machine learning, statistical modeling, data engineering, and analytical programming, giving learners the theoretical and technical foundation needed to solve complex data problems. Through hands-on coding exercises, quantitative reasoning, and exposure to real-world datasets, students learn to build predictive models, interpret patterns, and evaluate the performance of data-driven systems. This structure supports the development of strong analytical thinking and prepares learners to approach data challenges with confidence.
In addition to conceptual depth, the program emphasizes practical application through project-based coursework, cloud computing tools, and interactive online collaboration. Students strengthen competencies in data visualization, big data processing, algorithmic thinking, and applied analytics while working in virtual teams that simulate professional data environments. Engagement with industry tools, case-based analysis, and emerging technologies such as distributed computing and AI integration helps learners understand how data science supports decision-making across business, science, and public sectors. By blending theoretical knowledge with hands-on skill building, the program equips graduates to apply data-driven solutions effectively in a variety of professional contexts.
Key information
Key Facts
- Program Title: Data Science
- Degree Type: Master of Science
- Duration: 1,5 years
- Mode of Study: Part-time, Online
- Application Deadline: 13 January 2026
- Location: Northwestern University, United States
- Field of Study: Data Science & Big Data
- Language of Instruction: English
Program Structure
Semester 1 – Foundations of Data Science, Programming & Statistical Analysis
• Statistical Methods and Probability
• Programming for Data Science (Python / R)
• Data Wrangling and Preprocessing
• Data Visualization and Communication
Semester 2 – Machine Learning, Big Data & Analytics Tools
• Machine Learning Algorithms
• Big Data Engineering and Distributed Systems
• Database Systems and Data Pipelines
• Applied Analytics Project I
Semester 3 – Advanced Modeling, AI Integration & Capstone
• Deep Learning and Neural Networks
• AI Applications and Ethical Considerations
• Advanced Predictive Modeling
• Data Science Capstone Project
Career Opportunities
Graduates of this program are prepared for analytical, engineering, and modeling roles across industries where data drives strategic and operational decisions. Many professionals work in technology companies, finance and banking, health analytics, and research institutions, contributing to predictive modeling, data architecture, algorithm development, and digital transformation initiatives. Responsibilities may include building machine learning models, processing large datasets, developing data pipelines, creating dashboards, performing exploratory analysis, and collaborating with cross-functional teams to support evidence-based strategy. With strong training in computational methods and applied analytics, graduates are also well suited for roles in business intelligence, AI engineering, quantitative analysis, and cloud-based data solutions. The program additionally provides a foundation for doctoral study or specialized data science certifications.
Why Choose This Program
This program is ideal for students who want to gain deep technical expertise in data science while benefiting from the flexibility of an online, part-time format. Its curriculum emphasizes computational mastery, applied analytics, and modern machine learning, offering a clear progression from foundational skills to advanced AI-driven modeling. Over 1.5 years, students gain experience with industry-standard tools, real-world datasets, and collaborative virtual environments that mirror professional workflows. The program’s combination of rigorous coursework, hands-on projects, and a capstone experience helps learners build a strong, practical portfolio that demonstrates readiness for competitive data-focused roles. For individuals aiming to shape data-driven innovation in any sector, this program provides a highly relevant and future-oriented academic pathway.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 312 555 2040
Email: admissions@northwestern.edu
Address: University of Northwestern, 633 Clark Street, Evanston, IL 60208, United States
