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Computer Science (Post-Bacc)

Certificate
What is the Post-Baccalaureate 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 a Post-Baccalaureate Certificate in Computer Science?
Frequently Asked Questions
Tuition, Financial Aid, and Scholarships
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 Post-Baccalaureate Certificate in Computer Science?

The Post-Baccalaureate Certificate in Computer Science at Tufts University is an on-campus program for students and professionals who hold at least a bachelor’s degree and have limited prior coursework in computer science. Students complete five Tufts courses to build foundational knowledge in data structures, discrete mathematics, computing systems, algorithms, and related areas.

The certificate is available through full-time or part-time study on the Medford/Somerville campus and is typically completed in 9 to 24 months. Students may use this preparation to pursue professional opportunities that require computing knowledge or to apply to the M.S. in Artificial Intelligence, M.S. in Computer Science, or M.S. in Cybersecurity at Tufts.

 Who is this Program For?

The Post-Baccalaureate Certificate in Computer Science is designed for applicants with at least a bachelor’s degree who have completed few computer science courses and want to build foundational preparation in the field.

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

  • Develop a foundation in computer science through on-campus study
  • Prepare for professional opportunities that require computing knowledge
  • Build preparation for graduate study in artificial intelligence, computer science, or cybersecurity
  • Study data structures, discrete mathematics, computing systems, algorithms, and software concepts
  • Pursue a structured pathway toward an M.S. in Artificial Intelligence, M.S. in Computer Science, or M.S. in Cybersecurity at Tufts

Applicants who already have substantial preparation in computer science and want graduate-level specialization should explore the Certificate in Computer Science.
 

Application Requirements

  • Application Fee
  • Resume/CV
  • Personal Statement
  • Transcripts
  • One letter of recommendation (Certificate Track) or three letters of recommendation (Master's Track)
  • GRE scores (if applicable)
    • GRE scores are no longer required for candidates with an undergraduate degree from an accredited U.S. or Canadian institution. GRE scores are required for applicants who don't have a degree from a U.S. institution.
  • 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)
  • Portfolio (optional)

Apply  Request Info 

 What Will You Study?

Students complete five Tufts courses that provide foundational preparation across core areas of computer science.

Required Courses

  • CS 15: Data Structures
  • CS 61, MATH 61, or MATH 65: Discrete Mathematics

Competency-Area Courses

Students choose two courses from two distinct competency areas:

  • Computer architecture and assembly language
  • Programming languages
  • Data structures and analysis of algorithms
  • Theory of computation

Elective Course

Students complete one additional computer science elective above CS 15, subject to program requirements. Students who do not have previous programming coursework may begin with CS 11: Introduction to Computer Science as prerequisite preparation. Completion of the program requires grades of B- or better in all certificate courses.

Through this coursework, students build knowledge in areas such as:

  • Programming and computational problem-solving
  • Data structures
  • Discrete mathematics
  • Computer architecture and systems
  • Programming languages
  • Algorithms
  • Theory of computation

About the Department of Computer Science

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

Students build foundational computing knowledge within a department connected to interdisciplinary applications of computer science across engineering, science, health, and society.

Apply  Request Info 

 Why Study Computer Science at Tufts?

 

Designed for Students Entering Computer Science

The program is structured for applicants who have already earned a bachelor’s degree but have completed few computer science courses. Students develop foundational preparation through a focused five-course curriculum.
 

Core Preparation Across Computing Areas

Students study data structures and discrete mathematics, then expand their foundation through courses in distinct competency areas and an additional elective. This structure supports preparation for continued study in computer science or related fields.

Pathways to Master’s Study

The post-baccalaureate certificate can prepare students to apply to the M.S. in Artificial Intelligence, M.S. in Computer Science, or M.S. in Cybersecurity at Tufts. Eligible graduate-level coursework completed in the certificate may be eligible to count toward a master’s degree upon acceptance to the master’s program.
 

On-Campus Study in Greater Boston

Students complete the program on Tufts’ Medford/Somerville campus, near Boston and Cambridge technology, research, and innovation communities. This location connects computer science study with a region known for software, artificial intelligence, cybersecurity, and health technology.

 What Can You Do With a Post-Baccalaureate Certificate in Computer Science?

The Post-Baccalaureate Certificate in Computer Science can support students and professionals who want to build foundational computing knowledge for new professional directions or continued education.

Students may use this credential to strengthen preparation relevant to:

  • Software and computing applications
  • Data-focused technical work
  • Systems and hardware concepts
  • Algorithms and computational problem-solving
  • Graduate study in artificial intelligence, computer science, and cybersecurity
  • Related computing and technology fields

 Frequently Asked Questions

 

How Many Courses Are Required for the Post-Baccalaureate Certificate in Computer Science?

Students complete five Tufts courses: data structures, discrete mathematics, two courses from distinct computer science competency areas, and one additional computer science elective above CS 15.
 

What is the Difference Between the Post-Baccalaureate Certificate and the Certificate in Computer Science?

The Post-Baccalaureate Certificate in Computer Science is designed for applicants who need foundational computer science preparation. The Certificate in Computer Science is designed for applicants who already have computer science preparation and want graduate-level study in a specialty area.

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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