Award-Winning Computer Science Tutors
serving Barnstable, MA

Studying computer science at MIT, Brice digs into everything from data structures and algorithms to systems-level thinking with students at any stage. He's tutored over 30 students in the past year alone, tackling topics like recursion, object-oriented design, and algorithmic complexity. Rated 4.9 by students.

Studying computer science since before college and now pursuing a master's at UMass Amherst, Milo covers the full stack — from data structures and algorithms to systems-level concepts like memory management and concurrency. He spent three years in his university's tutoring center breaking down topics like recursion, sorting complexity, and graph traversal for students at every level.

As a computer science major at Boston University, Irene is immersed in the subject daily — from data structures and algorithms to object-oriented design. She breaks down abstract programming concepts into concrete steps, walking through how to trace logic, debug code, and think like a developer rather than just memorize syntax.

Between Java, Python, and the AP Computer Science A curriculum, William covers the languages and frameworks that most high school and intro-level college students actually encounter. His Northeastern CS program keeps him close to the material — he's working through the same data structures, algorithms, and OOP principles his students are learning, which means he can pinpoint exactly where a concept like recursion or inheritance starts to feel slippery. Rated 5.0 by students.

A working software developer with a BS in Computer Science, Andy covers core CS topics — data structures, algorithms, recursion, Big-O analysis — with the perspective of someone who uses them daily in mobile application design. He explains not just how an algorithm works but why you'd choose it over alternatives in a real codebase.

Allison holds a B.S. in Computer Science from Mount Holyoke College, so she's been through the full gauntlet — from writing first programs to tackling data structures, algorithms, and debugging logic that refuses to cooperate. She teaches coding concepts by building up from how the computer actually processes instructions, which makes abstract ideas like recursion and iteration far more intuitive.

As a computer science major heading into her senior year, Allison is deep in the material students are encountering for the first time — data structures, algorithm analysis, object-oriented design. She explains concepts like recursion and Big-O notation by building up from simple examples in Python before introducing the formal definitions, which makes abstract ideas click faster.

Christine is a third-year CS student at Northeastern who lives this material daily — from data structures and algorithms to object-oriented design and recursion. She walks through problems by connecting the abstract logic to concrete code, so concepts like linked lists or graph traversals click rather than feel like rote memorization. Rated 4.9 by students.

An Electronic Design degree from Hampshire College means Micah lives at the intersection of code and hardware — he's built electronics curricula and understands programming as a tool for making things work in the real world. He tackles core CS concepts like control flow, data structures, and debugging by grounding them in tangible projects rather than abstract exercises.

Studying computer science at Tufts alongside civil engineering gives Adam a dual perspective — he understands both the theoretical foundations like data structures and algorithms and how code gets applied to solve real-world problems. He unpacks concepts like recursion, object-oriented design, and sorting algorithms by building small programs that make abstract ideas concrete. That hands-on approach clicks especially well for students who learn by doing.

Adriano leans into the proof-based, mathematical side of computer science — the discrete math foundations, formal logic, and algorithmic correctness arguments that many introductory courses rush past. As an MIT CS undergrad, he's immersed in that rigor daily and brings it to sessions where students need to understand not just what an algorithm does but how to prove it works.

I'm Cindy! I'm a freshman at Harvard University and graduated from San Mateo High School this past year. I love to teach and have years tutoring students of all ages in a variety of subjects. Feel free to send me a message if you have any questions or would like to schedule a tutoring session!

I'm Connor, a computer science, linguistics, and Japanese major at the University of Massachusetts Amherst. I'm in my third year expecting to graduate in May next year.

I am passionate about helping students succeed in computer science by making complex concepts clear and engaging. With over seven years of teaching experience in higher education, I have taught a range of courses in programming and information systems. I hold a Master's degree in Computer Science from the University of Trento, Italy, and a Bachelor's degree in Information Systems from Addis Ababa University, Ethiopia, and I am currently pursuing my Ph.D. in Computer Science. My favorite subjects to tutor are C++, Java, and Systems Analysis and Design because they build strong problem-solving and analytical skills. I focus on creating an interactive, supportive learning environment that helps students gain confidence and apply their knowledge. Outside of academia, I am interested in pursuing roles in the tech industry as a system analyst or software engineer.

From data structures and algorithms to systems-level thinking, computer science covers enormous ground. John earned a BS in Computer Science and codes in Java, C++, and SQL, giving him the range to dig into whatever topic is causing trouble — whether that's recursion, Big-O analysis, or database design.

Corrina's mechanical engineering degree required extensive programming coursework, and she now teaches core computer science concepts — data structures, algorithms, Boolean logic, and computational thinking — in a way that makes abstract ideas tangible. She connects each concept to real applications, whether that's sorting algorithms in a search engine or conditionals inside a robot's control loop.

From basic programming constructs all the way up to computational analysis and finite automata, Andrew has tutored the full range of computer science topics at both the high school and college level. His CS degree gives him the depth to explain not just how an algorithm works but why its time complexity matters. Rated 5.0 by students.

Studying both chemical engineering and computer science at Cornell gives Jonathan an unusual angle on programming — he's constantly writing code to solve quantitative, real-world problems rather than just completing standalone assignments. That dual perspective makes him especially effective at teaching algorithmic thinking and Java or Python fundamentals, since he can show students how CS concepts like iteration and data manipulation actually get applied in technical fields outside of software development.

Isabella TA'd multiple computer science courses at MIT, so she's seen exactly where students get stuck — whether it's tracing recursive calls, understanding how data structures like linked lists and trees actually work in memory, or debugging logic errors in their code. She explains the underlying concepts so that writing correct programs becomes intuitive rather than trial-and-error. Rated 5.0 by students.

David's CS degree and hands-on Python experience mean he can take students from writing their first loop to tackling recursion, data structures, and algorithm design. He emphasizes explaining your reasoning — not just getting code to compile — because understanding why a solution works is what separates students who memorize syntax from those who can actually think like programmers. Rated 5.0 by students.

Building AI systems and low-level software at Stanford — in both Python and C++ — Kevin knows where the theoretical meets the practical in computer science. His biocomputation specialization means he can explain not just how to implement an algorithm, but why certain computational approaches work better for different problem domains. Rated 5.0 by students.

Jeff tackles computer science by connecting abstract concepts like recursion, data structures, and algorithmic complexity to concrete problem-solving steps students can follow. His science background means he's comfortable with the mathematical logic underlying CS, from Boolean algebra to Big-O analysis.

Biomedical engineering at Rice requires heavy computational coursework, so Theresa has tackled core computer science concepts — from object-oriented programming and data structures to algorithm complexity — in the context of solving real problems. She explains abstract ideas like recursion and sorting algorithms by connecting them to concrete examples rather than letting students drown in theory. Rated 5.0 by students.

Pursuing a CS master's at Penn while TAing discrete math means Keenan lives in both the theoretical and practical sides of computer science every day. He unpacks core topics like algorithm complexity, data structure tradeoffs, and computational logic in a way that connects abstract ideas to real code. Rated 5.0 across all sessions.

Ryan is a computer science major at Cornell, which means he's actively working through the same core curriculum — algorithms, data structures, computational complexity — that college CS students encounter. He explains concepts like recursion, Big-O analysis, and graph traversal by tracing through concrete examples rather than relying on abstract definitions. Rated 4.8 across his sessions.

Allison's CS degree from Dartmouth means she's worked through the full arc — from writing first programs to tackling data structures, algorithms, and computational theory. She unpacks abstract concepts like recursion and Big-O analysis by walking through concrete code examples, making the logic visible before the notation takes over.