Award-Winning Computer Science Tutors
serving Cincinnati, OH

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.

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.

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 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.

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.

From recursion and sorting algorithms to Big-O analysis and object-oriented design, Ethan covers core computer science concepts with the rigor of someone studying it as a second major alongside aerospace engineering. He emphasizes understanding why an algorithm works — tracing through execution step by step — so students can adapt their thinking to new problems on exams and in projects.

Margaret studies Computer Science at Stanford alongside Political Science, giving her a broad perspective on how computational thinking applies beyond just writing code. She breaks down core topics like data structures, algorithms, and recursion by connecting each one to real problems students can visualize. Rated 4.8 by her students.

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.

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.

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.

Between his AP Computer Science 5 and his engineering coursework at Vanderbilt, William has written code across contexts — from introductory Java to computational modeling in his chemical engineering classes. He breaks down abstract concepts like recursion, data structures, and algorithm efficiency by walking through concrete examples line by line. Students who can follow the logic but freeze when writing code from a blank screen tend to gain traction quickly with his approach.

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.

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.

Alston is pursuing a Computer Science degree at the University of Virginia, which means he's actively working through data structures, algorithms, and object-oriented design — not recalling them from years ago. He breaks down concepts like recursion and sorting algorithms by walking through the logic step by step, letting students trace the code themselves until the pattern clicks.

Benjamin's finance and economics training at Notre Dame means he learned to code as a problem-solving tool — building models, analyzing datasets, and automating calculations — rather than through a traditional CS curriculum. That pragmatic entry point makes him effective at teaching programming logic and computational thinking to students who want to understand how code actually gets used in business and quantitative fields. Rated 5.0 by students.

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 automata theory and computational complexity to practical algorithm design, Firas covers computer science as both a theoretical discipline and a hands-on craft. His Ph.D. research at the intersection of machine learning and big data means he can connect abstract CS concepts — graph traversals, runtime analysis, NP-completeness — to the systems that actually use them. Rated 5.0 by students.