Award-Winning Computer Science Tutors
serving Cleveland, OH

Between his CS degree at Case Western Reserve and running a web design business, Brian writes code in both academic and real-world contexts every day. He unpacks foundational topics like data structures, sorting algorithms, and recursion by connecting them to practical applications — showing why a hash map outperforms a list search, or how recursion models real problems like file system traversal.

Software development taught Michael something that textbooks often skip: the discipline of decomposing a massive, ambiguous problem into small, testable pieces — and that's exactly how he teaches computer science. His professional coding experience across languages like Java, Python, Ruby, and C means he can ground abstract topics like object-oriented design or control flow in real working code rather than classroom-only exercises. Rated 4.9 by students.

I'm a recent college graduate with degrees in Biological Sciences and Russian from Ohio University. During my time there, I tutored students in a variety of subjects, including biology, chemistry, and Spanish. In addition, I worked as both a peer advisor and teaching assistant, which gives me insight into the learning strategies and study skills that students need to succeed. As a tutor, I like to focus on doing actual problems with students because it is the most effective way to immediately identify their strengths and weaknesses and to address them. In my free time, I like to lift weights, read books, and spend time with my friends.

I am a recent graduate with a master's in electrical engineering from Case Western Reserve University. I won the Bill and Melinda Gates Millennium Scholarship which covers full tuition up to Ph.D. I was on the Dean's List for three consecutive years. Additionally, I won the OZY Media Genius Award in 2015 to work on high-temperature superconductors. I currently work as a Technology Analyst at Accenture. I am also seriously considering whether I should go for a Ph.D. or not.

Between his engineering curriculum and competition math background, Kevin tackles computer science from both the theoretical and applied sides — algorithm complexity, recursion, sorting strategies, and how hardware constraints shape software decisions. He's especially effective at translating the mathematical foundations of CS into intuition students can actually use when writing and debugging code.

Studying computer science engineering at Ohio State with honors, Samuel digs into the discipline well beyond surface-level coding — think algorithm complexity, memory management, and how data structures like hash maps and trees actually work under the hood. He connects abstract CS theory to real implementations so the concepts stick long after the exam.

Two years writing computerized tasks for Ohio State's Clinical Neuroscience Laboratory taught Luke how to translate experimental logic into working code — structuring programs around precise conditions, variables, and outcomes. That lab experience, combined with his Java and AP Computer Science teaching, means he approaches programming as applied problem-solving rather than abstract syntax drills. Rated 4.8 by students.

I am passionate about the subject, they may feel that they can tap into that passion. Second, I like to engage the student personally. Education can sometimes feel transactional or even coercive. I want my student to feel that I am working for their benefit, and because I care about them, not because I'm getting paid.

I am passionate about teaching because I love helping someone understand and become confident in a concept that previously baffled them. I am a student at The Ohio State University working towards a Computer Science degree. I have experience tutoring math up through AP Calculus BC, French, and AP Literature. My experience in tutoring comes from the free weekly French tutoring program I initiated at my high school, which grew to me tutoring other subjects as well. My teaching philosophy involves discussion and helping the student come to an answer themselves, which allows the topic to stick. Because of this one of my favorite subjects to tutor is writing. Writing tutoring helps the student grow and allows them to see the problems in their writing themselves. Outside of academia I enjoy calligraphy and playing piano.

I am currently pursuing my B.S. in microbiology as a pre-medical student with hopes to attend medical school.

A Stanford MS in Computer Science means David can teach everything from data structures and algorithms to object-oriented design with the depth that comes from building real systems — not just reading about them. He spent a summer teaching web and app development to high school students in Palestine, so he knows how to make abstract CS concepts click through hands-on projects.

Earning a computer science minor at Penn meant Cody went deep on data structures, algorithms, and programming logic alongside students in one of the country's top CS programs. His cognitive science major adds an unusual edge: he understands how people learn to think computationally, which makes him effective at explaining recursion, sorting algorithms, or Big-O analysis in ways that actually stick.

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.

From sorting algorithms to recursion to object-oriented architecture, computer science rewards the ability to think in layers of abstraction. Joel is pursuing CS at Cornell alongside physics, which means he approaches programming problems with both mathematical rigor and practical debugging instincts. He's comfortable across Python and Java and adapts to whatever language a student's course requires.

Pursuing both computer science and data science at NYU's Courant Institute with a cybersecurity minor, Diego lives in this material daily — from algorithms and data structures to networking and systems-level thinking. He breaks abstract CS concepts into smaller, buildable pieces so students can trace the logic themselves rather than just copying solutions.

Earning a certificate in Statistics and Machine Learning at Princeton gave Julie hands-on experience with core computer science concepts — algorithm design, data structures, and computational complexity. She approaches CS the way she approaches philosophy: by asking students to reason through *why* a solution works, not just whether it compiles.

Eric treats coding problems the same way he treats logical puzzles — by breaking them apart, finding the pattern, and building a solution step by step. As a CS major at Washington University in St. Louis, he's deep in Java and JavaScript right now, which means he can walk students through everything from writing their first function to structuring a full object-oriented program. His approach emphasizes learning to think through problems algorithmically before jumping to syntax.

Engineering science at Vanderbilt means Ethan writes code to solve real problems — simulations, data analysis, algorithm design — not just textbook exercises. He breaks down core concepts like recursion, data structures, and object-oriented design by connecting them to projects that actually do something interesting.

Trained in computer science at UT Austin and currently pursuing a PhD that blends computational methods with social science, David brings both theoretical depth and applied versatility to CS instruction. He digs into core topics like algorithm analysis, data structures, and computational complexity, connecting them to the kind of real-world problem-solving that makes the discipline click.

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.

Julia is a computational science major at Stanford who writes code daily and understands the gap between knowing syntax and thinking like a programmer. She digs into core concepts like recursion, data structures, and algorithm design by walking through problems step by step until the logic becomes intuitive. Students learning Python, Java, or tackling their first real debugging challenge get someone who can explain the *why* behind every line.

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.