Complex network analysis is the quantitative study of interconnected systems that influence every aspect of our lives—from where we get our news and who we share ideas with, to how we travel and the people we interact with, to the products we purchase and the foods we eat. Networks are ubiquitous across natural and human-made systems, and their structure and dynamics can explain and help improve the greatest challenges of the next century such as pandemics, food scarcity, cultural polarization, and climate change. Expertise in the emerging field of complex network analysis, within the landscape of the rapid growth of artificial intelligence and machine learning, forms the foundation of the next generation of thought leaders. Northeastern University leads the way in this burgeoning field, offering a unique master's degree program in complex network analysis methodologies. The program is designed to equip students with the conceptual and analytical tools needed to find patterns of connections in networked systems and apply these techniques in real-world settings. The curriculum includes industry-aligned concentration areas of focus, enabling graduates to apply complex network analysis skills in impactful careers in the public and private sectors as well as in research. The concentrations for this program correspond directly to the following industry sectors:
- Public health and life sciences fields such as epidemiological modeling, public policy, and behavioral research
- Social or urban science and research fields such as urban planning, social network research, economics, education, criminal science, or public policy
- Finance or technological fields such as financial analytics, market research, or network analysis for business
- Biological systems modeling used across research and industry including network biology, drug discovery, or multi-omics mining
In this degree program, students are admitted to the college associated with their concentration, and their degree is awarded by that college. The concentrations are associated with the following colleges:
- Complex Biological Networks—College of Science
- Complex Social Systems—College of Social Sciences and Humanities
- Economic and Technological Networks—Khoury College of Computer Sciences
- Population Health Dynamics—Bouvé College of Health Sciences
Students will follow all policies associated with their home college.
Beginning with students admitted in the fall of 2026, all students pursuing on-ground master's degree programs must complete a university-level experiential learning requirement. This requirement may be fulfilled through the curriculum, co-op, or other work- or industry-integrated learning experiences.
Complete all courses and requirements listed below unless otherwise indicated.
Required Courses
Course List | Code | Title | Hours |
| CNET 5050 | Fundamentals of Complex Networks | 4 |
| CNET 5051 | Analyzing Complex Network Data | 4 |
| CNET 5052 | Advanced Tools for Complex Network Analysis | 4 |
| CNET 5901 | Visualizing Complex Networks | 2 |
| CNET 5902 | Communicating Network Data | 2 |
Concentrations
Complete one of the following concentrations:
Experiential Courses
Course List | Code | Title | Hours |
| 4 |
| Complex Network Analysis Research Rotation | |
| Complex Network Analysis Capstone | |
| Thesis | |
| Directed Study | |
Program Credit/GPA Requirements
Minimum 33 total semester hours required
Additional hours may be required based on student choice of courses or concentration.
One semester hour of additional coursework is required for participation in co-op.
Minimum 3.000 GPA required
Concentration in Complex Biological Networks—College of Science
Course List | Code | Title | Hours |
| |
| CNET 5515 | Complex Network Analysis for Biological Systems | 4 |
| 8 |
| Bioinformatics Programming | |
| Algorithmic Foundations in Bioinformatics | |
| Introduction to Bioinformatics | |
| Foundations in Biotechnology | |
| Population Dynamics | |
| Geographical Information Systems | |
| Applied Social-Ecological Systems Modeling | |
| Advanced Biostatistics | |
| Advanced Spatial Analysis | |
| Foundations of Statistical Theory and Probability | |
| Introduction to Mathematical Methods and Modeling | |
| Statistical Learning | |
| Statistics for Bioinformatics | |
| Introduction to Scientific Computing | |
| 4 |
| Spreading on Networks: From Epidemics to Memes | |
| Complexity in Social Systems | |
| Financial and Economic Networks | |
| Special Topics in Complex Networks | |
| |
| EESC 6500 | Pathways to Professional Success | 1 |
| EESC 6964 | Co-op Work Experience | 0 |
| or EESC 6954 | Co-op Work Experience - Half-Time |
| or EESC 6965 | Co-op Work Experience Abroad |
Concentration in Complex Social Systems—College of Social Sciences and Humanities
Course List | Code | Title | Hours |
| |
| CNET 5314 | Complexity in Social Systems | 3 |
| 6 |
| Sports Analytics Through Data and Networks | |
| Introduction to Computational Statistics | |
| Agent-Based Modeling for Applied and Social Sciences | |
| Research Methods in the Social Sciences | |
| Modeling and Analyzing Social Networks | |
| Analyzing Complex Digitized Data | |
| Statistical Analysis | |
| Introduction to Scientific Computing | |
| Big Data for Cities | |
| Advanced Spatial Analysis of Urban Systems | |
| 4 |
| |
| Spreading on Networks: From Epidemics to Memes | |
| Financial and Economic Networks | |
| Complex Network Analysis for Biological Systems | |
| Special Topics in Complex Networks | |
| |
| EESH 6000 | Professional Development for Co-op | 0 |
| INSH 6964 | Co-op Work Experience | 0 |
Concentration in Economic and Technological Networks—Khoury College of Computer Sciences
Course List | Code | Title | Hours |
| |
| CNET 5411 | Financial and Economic Networks | 3 |
| 7 |
| Sports Analytics Through Data and Networks | |
| Foundations of Artificial Intelligence | |
| Applied Programming and Data Processing for AI | |
| Reinforcement Learning and Sequential Decision Making | |
| Algorithms | |
| Data Mining Techniques | |
| Empirical Research Methods | |
| Deep Learning | |
| Statistical Methods for Computer Science | |
| Supervised Machine Learning and Learning Theory | |
| Unsupervised Machine Learning and Data Mining | |
| Foundations of Data Analysis for Business | |
| Introduction to Scientific Computing | |
| 4 |
| Spreading on Networks: From Epidemics to Memes | |
| Complexity in Social Systems | |
| Complex Network Analysis for Biological Systems | |
| Special Topics in Complex Networks | |
| CS 6964 | Co-op Work Experience | 0 |
| or CS 6954 | Co-op Work Experience - Half-Time |
| or CS 6965 | Co-op Work Experience Abroad |
| or CS 6955 | Co-op Work Experience Abroad - Half-Time |
Concentration in Population Health Dynamics—Bouvé College of Health Sciences
Course List | Code | Title | Hours |
| |
| CNET 5126 | Spreading on Networks: From Epidemics to Memes | 4 |
| 6 |
| Introduction to Epidemiology | |
| Biostatistics in Public Health | |
| AI at the Intersection of Health and Society | |
| Applied Regression Analysis | |
| Social Epidemiology | |
| Causal Inference 1 | |
| Advanced Methods in Biostatistics | |
| Causal Inference in Public Health Research | |
| Introduction to Scientific Computing | |
| 4 |
| |
| Complexity in Social Systems | |
| Financial and Economic Networks | |
| Complex Network Analysis for Biological Systems | |
| Special Topics in Complex Networks | |
| |
| HLTH 5101 | Professional Development for Bouvé Graduate Co-op | 1 |
| HLTH 6964 | Co-op Work Experience | 0 |
| or HLTH 6954 | Co-op Work Experience - Half-Time |
| or HLTH 6965 | Co-op Work Experience Abroad |
| or HLTH 6955 | Co-op Work Experience Abroad - Half Time |
