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Computer Science (Certificate)

Certificate
What is the Certificate in Computer Science?
Who is this Program For?
How Do You Apply?
What Will You Study?
Why Study Computer Science at Tufts?
What Can You Do With an Certificate in Computer Science?
Frequently Asked Questions
Apply Request Info
Application Deadlines
Fall: Jun 1
Spring: Sep 15
Summer: n/a
School/Department
Computer Science
Contact
gradadmissions@tufts.edu
Location
Medford/Somerville
Format
On-campus
Commitment Options
Full-time
Part-time
Average Duration
9 - 24 months
Credits
Varies

Overview

What is the Certificate in Computer Science?

The Certificate in Computer Science at Tufts University is a four-course graduate certificate designed for students and professionals who already have preparation in computer science and want to deepen their knowledge in a focused area of the field. Students create a specialized course plan using graduate Computer Science offerings and selected special topics courses.

The program is offered on campus in Medford/Somerville and may be completed through full-time or part-time study. Students typically complete the certificate in 9 to 24 months.

 Who is this Program For?

The Certificate in Computer Science is designed for applicants with at least a bachelor’s degree in Computer Science or a closely related field with approved work experience.

This program may be a strong fit for applicants who want to:

  • Build advanced knowledge in a computer science specialty area
  • Update or broaden existing computing expertise
  • Study topics such as algorithms, artificial intelligence, machine learning, cybersecurity, cloud computing, data systems, human-computer interaction, or software systems
  • Pursue graduate Computer Science coursework without immediately enrolling in a master’s degree
  • Prepare for possible continuation into the M.S. in Computer Science at Tufts

Applicants seeking introductory computer science preparation rather than graduate-level specialization should explore the Post-Baccalaureate Certificate in Computer Science.
 

Application Requirements

  • Application Fee
  • Resume/CV
  • Personal Statement
  • Transcripts
  • One letter of recommendation
  • Official TOEFL, IELTS, or Duolingo test scores (if applicable)
    • Competitive scores for the Department of Computer Science are below:
      • TOEFL Total: 100 (Reading: 26, Listening: 26, Writing: 22, Speaking: 25)
      • IELTS Total: 7.5 (Minimum of 7.0 for each subscore)
      • Duolingo Total: 120 (Literacy: 125, Conversation: 120, Comprehension: 135, Production: 105)

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 What Will You Study?

Students complete four graduate-level courses in Computer Science and may cluster their coursework around a particular interest or research area.

Courses may be selected from regular Computer Science department offerings or from COMP 150 Special Topics offerings. Depending on course availability and academic goals, students may explore areas such as:

  • Algorithms and data structures
  • Artificial intelligence and machine learning
  • Cloud computing and distributed systems
  • Computer vision
  • Cybersecurity and privacy
  • Data visualization and databases
  • Human-computer interaction and human-robot interaction
  • Operating systems and networks
  • Programming languages and software engineering
  • Computational biology

About the Department of Computer Science

The Certificate in Computer Science is offered through the Department of Computer Science at Tufts University School of Engineering. The department supports graduate study across areas including artificial intelligence, machine learning, data science, cybersecurity, computational biology, human-computer interaction, human-robot interaction, software systems, algorithms, visualization, and networked systems.

Students can select coursework that aligns with their professional interests or intended area of advanced study while learning in a department connected to interdisciplinary computing applications across Tufts.

Apply  Request Info 

 Why Study Computer Science at Tufts?

 

Customizable Graduate Coursework

Students complete four graduate Computer Science courses selected around an area of interest. This flexible structure supports focused study in areas such as artificial intelligence, security, systems, data, algorithms, visualization, or human-centered computing.
 

Practical Computing Perspectives

Students pursue advanced computer science study with attention to how computational methods are designed, evaluated, and applied in real-world contexts. Coursework can help students strengthen technical problem-solving skills relevant to building reliable, effective, and responsible computing solutions.

Interdisciplinary Computer Science Environment

Computer science at Tufts connects with fields including engineering, biology, health, robotics, psychology, data science, and human-computer interaction. Students can build technical knowledge relevant to complex problems that cross disciplinary boundaries.
 

Pathway to the M.S. in Computer Science

Computer Science certificate courses may be transferable into the Tufts M.S. in Computer Science upon acceptance to the master’s program, allowing students who continue their graduate education to build on eligible certificate coursework.

 What Can You Do With a Certificate in Computer Science?

The Certificate in Computer Science can support students and professionals who want to deepen their existing computing knowledge or develop expertise in a specific technical area.

Students may use this credential to strengthen preparation relevant to areas such as:

  • Software development and software systems
  • Artificial intelligence and machine learning
  • Data systems and visualization
  • Cybersecurity and privacy
  • Cloud computing and distributed systems
  • Algorithms and computational methods
  • Human-computer interaction
  • Computational biology
  • Further graduate study in computer science or related fields

 Frequently Asked Questions

 

What Academic Background Is Appropriate for this Program?

Applicants should hold at least a bachelor’s degree in Computer Science or a closely related field with approved work experience. Applicants seeking foundational preparation in computer science should explore the Post-Baccalaureate Certificate in Computer Science.
 

Can I Customize My Certificate Coursework?

Yes. Students may cluster their coursework around a computer science interest or specialty area using regular department courses or approved COMP 150 Special Topics offerings.

Are Scholarships Available?

The School of Engineering offers partial tuition scholarships for a select group of Engineering master’s and certificate programs. When you apply for admission, you’ll automatically be considered, there’s no separate scholarship application or additional information required. Applicants are encouraged to apply early for priority scholarship consideration.
 

How Do I Apply?

Applicants can apply online through Tufts Graduate Admissions Portal. Required materials typically include transcripts, a resume or CV, letters of recommendation, and a statement of purpose. International applicants may also need to submit English proficiency documentation. Visit the admissions page for current deadlines and application requirements.

Faculty

faculty photo

Jeffrey Foster

Professor and Chair of Computer Science
Computer Science
Programming languages, software engineering, security
faculty photo

Marty Allen

Teaching Professor
Computer Science
Artificial intelligence, machine learning, reinforcement learning.
faculty photo

Ankit Bhardwaj

Assistant Professor
Computer Science
low-latency and highly scalable datacenter systems
faculty photo

Remco Chang

Professor
Computer Science
Data visualization, visual analytics, human-computer interaction, databases, computer graphics
faculty photo

Ming Chow

Teaching Professor
Computer Science
cyber security
faculty photo

Alva Couch

Associate Professor
Computer Science
data science, software systems engineering, performance analysis, system, network, and data management
faculty photo

Lenore Cowen

Professor
Computer Science
computational molecular biology, data science, graph algorithms, network science, discrete mathematics
faculty photo

Ethan Danahy

Research Associate Professor
Center for Engineering Education Outreach
design, implementation, and evaluation of different educational technologies
faculty photo

J.P. de Ruiter

Professor of Psychology and Computer Science
Psychology
Cognition and Psycholinguistics
faculty photo

Fahad Dogar

Associate Professor
Computer Science
Improving performance and reliability of networked systems, specifically cloud-based systems, mobile and wireless systems, and the Internet. Also, interested in designing technologies for developing regions.
faculty photo

Karen Edwards

Assistant Teaching Professor
Computer Science
low-dimensional geometric topology
faculty photo

Soha Hassoun

Professor
Computer Science
Machine Learning for Systems Biology; Metabolic Engineering, computer-aided design for integrated circuits
faculty photo

Michael Hughes

Wittich Family Assistant Professor
Computer Science
Machine learning : probabilistic models, Bayesian inference, variational methods, time-series analysis, semi-supervised learning Clinical informatics : electronic health record analysis
faculty photo

Robert Jacob

Professor
Computer Science
human-computer interaction, new interaction modes and techniques, implicit brain-computer interfaces, user interface software
faculty photo

Dave Lillethun

Assistant Teaching Professor
Computer Science
computer science education, distributed systems, operating systems, networked systems, software development, secure systems and networking
faculty photo

Liping Liu

Associate Professor
Computer Science
Machine Learning, Data Science, Deep Learning, Generative Models, Time Series, Graph Learning
faculty photo

Noah Mendelsohn

Professor of the Practice
Computer Science
distributed systems, operating systems, World Wide Web
faculty photo

Megan Monroe

Associate Teaching Professor
Computer Science
data, visualization, language
faculty photo

Raja Sambasivan

Ankur and Mari Sahu Assistant Professor
Computer Science
Cloud computing, evolvability, debugging distributed systems.
faculty photo

Matthias Scheutz

Karol Family Applied Technology Professor
Computer Science
Artificial intelligence, artificial life, cognitive modeling, foundations of cognitive science, human-robot interaction, multi-scale agent-based models, natural language understanding.
faculty photo

Mark Sheldon

Teaching Professor
Computer Science
programming languages, software systems, concurrency, distributed information systems
faculty photo

Elaine Short

Assistant Professor
Computer Science
human-robot interaction, accessibility, robotics, human-in-the-loop machine learning, assistive technology Applying human-centered design and disability community values to the development, deployment, and evaluation of AI and machine learning for robotics, including: human-centered human-in-the-loop machine learning; disability-friendly assistive robotics; autonomous HRI in groups, public spaces, and other human-human contexts; and accessibility and disability inclusion in robotics education and the computing research community.
faculty photo

Jivko Sinapov

Associate Professor
Computer Science
Artificial Intelligence, Developmental Robotics, Computational Perception, Robotic Manipulation, Machine Learning, Human-Robot and Human-Computer Interaction
faculty photo

Donna Slonim

Professor
Computer Science
data science, algorithms for analysis of biological networks, gene and pathway regulation in human development, algorithms for precision medicine, computational approaches to pharmacogenomics and drug discovery or repositioning
faculty photo

Diane Souvaine

Professor
Computer Science
computational geometry, design and analysis of algorithms, computational complexity
faculty photo

Richard Townsend

Associate Teaching Professor
Computer Science
functional languages, compilers for embedded systems, program analysis and optimization, embedded domain-specific languages
faculty photo

Daniel Votipka

Lin Family Assistant Professor
Computer Science
computer security and privacy, secure development, security professionals, human-computer interaction, mobile security

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