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 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.

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.

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.

Most CS tutors come from pure software backgrounds — Clive's path runs through economics at Brown, where he picked up Java, Python, JavaScript, SQL, and HTML as tools for data analysis and building real projects rather than just completing problem sets. That applied angle makes him especially effective at teaching programming fundamentals and web technologies to students who learn better when code solves a tangible problem.

I am graduated from Penn State University in Industrial Engineering in 2017. I've tutored ever since I was in high school, and I love helping people! I like to help my students understand math (and other topics) instead of just doing it blindly. My goal is to help my students improve their math (and other topics) and build skills that will help them find learning easier in the future! Fun fact, I used to work for Disney and I like to salsa dance!

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 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.

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.

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.

From data structures and algorithms to computational complexity, Michelle covers the core CS curriculum with the depth you'd expect from a Duke CS graduate heading into a PhD at Michigan. She's especially strong at explaining abstract concepts like recursion and graph traversal by connecting them to concrete, visual examples that make the logic intuitive.

From data structures and algorithm analysis to the fundamentals of how operating systems and networks function, Nicholas covers computer science with the depth his Penn State CS degree provided. He's especially strong at explaining recursion, sorting algorithms, and Big-O notation — the concepts that separate students who can code from students who truly understand computation. Rated 5.0 by students.

From computer architecture and theory to parallel computing and machine learning, Brandon's master's coursework at RIT covers the full stack of computer science concepts. His two years of professional industry experience mean he can connect abstract topics — algorithm complexity, concurrency models, data structures — to how they actually show up in production code. Students rated him 4.9, which tracks with his ability to make dense CS material feel approachable.

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.

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.

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.