Award-Winning Computer Science Tutors
serving Durham, NC

Studying computer science at Duke means Susie is immersed in everything from algorithm analysis to systems design right now, which keeps her explanations current and grounded. She's especially sharp at connecting theoretical ideas like Big-O notation and recursion to the practical code students actually write. Co-founding a tutoring club in high school gave her early practice at making tough material click.

Florence doesn't just study computer science at Duke — she teaches it, having served as a TA for Intro to Databases and Computer Network Architecture while also interning in software development at IBM. That combination of academic depth and industry experience means she can explain everything from relational algebra to TCP/IP networking with concrete, real-world context. Rated 5.0 by students.

Studying computer science at UNC Chapel Hill means Jack lives in the material — algorithms, data structures, operating systems, and computational theory aren't abstract topics for him but daily coursework. He breaks down concepts like recursion, Big-O analysis, and memory management into intuitive explanations that stick.

Tackling a computer science minor alongside mechanical engineering at Duke, Shaan lives at the intersection of hardware thinking and software logic. He teaches core CS concepts — algorithm complexity, recursion, data structures, and object-oriented design — by connecting abstract ideas to concrete implementations, which is especially useful for students encountering Big-O notation or sorting algorithms for the first time.

Understanding computer science means thinking algorithmically: knowing not just that a sorting algorithm works, but why merge sort outperforms bubble sort at scale and how to analyze that difference with Big-O notation. Shourya codes in Python, C++, and MATLAB, which lets him adapt explanations to whichever language a student's course uses while keeping the focus on the underlying logic of data structures and algorithms.

I graduated from the University of North Carolina at Chapel Hill with a Bachelor of Science in Physics. I work with students in a variety of subjects, including Math, Physics, and Chemistry. I have experience working with students on the Autism spectrum and with ADHD.

I am a graduate student at George Mason University studying Computer Science. I also graduated at Vanderbilt University, with Bachelors Degrees in Computer Science, Mathematics, and Philosophy. When a student does not understand a topic or concept, I believe the best way to teach it is to meet students where they are at, providing individually catered feedback, and exploring the aspects of a student's weaknesses, finding a way to explain the concept in a way that resonates with and makes sense to the student. I am most familiar with tutoring for the SAT, where I have generally increased scores by 120-300 points.

I am a undergraduate freshman of the University of Michigan, studying business at the Ross School of Business. Working together with students and having a good time while seeing steady improvements has proven to provide me great joy. I believe that communication and relationship building is crucial for students to open up about their struggles and also for me to identify problems they don't realize they can improve on, so this is a key aspect of all of my lessons. During my free time, I enjoy playing sports or snacking on desserts while binge-watching Friends!

Three Bachelor of Science degrees — including Neuroscience — meant Anna was writing code long before she started teaching it, using Java, Python, and MATLAB to analyze data and build computational models across disciplines. That cross-field experience shapes how she teaches CS fundamentals: students don't just learn syntax, they learn to think about what a program needs to do before structuring it in any particular language. Rated 5.0 by students.

From sorting algorithms and Big-O analysis to data structures like linked lists and binary trees, Rhamy covers the foundational CS concepts that show up in coursework and technical interviews alike. His computer engineering degree at Vanderbilt, paired with experience in multiple languages, lets him explain abstract ideas through concrete code. Rated 5.0 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.

Holding both a B.S. in Computer Science from the University of Kentucky and a game development master's in progress at SCAD, Evan covers the full stack of CS fundamentals: data structures, algorithm analysis, object-oriented design, and software architecture. He connects abstract concepts like Big-O complexity or recursion to concrete implementations in C, C++, and Java so the theory actually sticks.

Studying Computer Science alongside Math/Stats at Carleton College, Thomas lives at the intersection of algorithms, data structures, and mathematical reasoning. He digs into topics like recursion, sorting algorithms, and object-oriented design by building understanding from first principles rather than rote code memorization.

Studying computer science at Cornell, Eric tackles everything from algorithm analysis and Big-O notation to systems-level concepts like memory management and recursion. He breaks down problems the way a CS student actually encounters them — whiteboarding a solution, tracing through edge cases, then translating logic into clean code. His 5.0 rating speaks to how clearly that approach lands.

Studying computer science at Cornell's College of Engineering, Ravnoor digs into topics like data structures, algorithms, and object-oriented design on a daily basis. He breaks complex problems — recursion, linked lists, sorting efficiency — into smaller, concrete steps so students build genuine understanding they can apply to new challenges independently.

Recursion, data structures, algorithmic complexity — these topics trip up students who try to memorize patterns without understanding why they work. Kevin holds both a bachelor's and master's in computer science from NYU, and he's the kind of tutor who will explain a concept three different ways until the logic genuinely lands. Rated 4.8 by students.

Michael earned his B.S. in Computer Science from UCLA, where he dug into everything from data structures and algorithms to software design principles. He breaks down abstract concepts like recursion, Big-O analysis, and object-oriented programming into concrete, step-by-step logic that clicks. He also teaches JavaScript, giving him a practical edge when students need to connect theory to actual code.

Philosophy trained Calin to build rigorous logical arguments; his math and CS degrees taught him to express that logic in C++ and JavaScript. That combination means he teaches programming concepts — from algorithm design to data structure selection — as exercises in precise reasoning, where every line of code follows from a clear chain of thought. 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.