Award-Winning Computer Science Tutors
serving Concord, CA

Learning to code is really learning to decompose problems, and that skill transfers whether the language is Java, Python, or something else entirely. Milan's CS degree grounds his teaching in fundamentals like control flow, data structures, and algorithmic complexity rather than surface-level syntax drills. He also draws on his English background to emphasize clear documentation and readable code.

Understanding data structures like arrays, linked lists, and sorting algorithms matters more than memorizing syntax — and that distinction is where Dennis spends most of his time. His background spans Java, JavaScript, and web development, so he can show how core CS concepts translate across languages and real projects.

Sarah's mathematics background means she's comfortable with the algorithmic and logical thinking that underpins computer science — concepts like recursion, Big-O analysis, and Boolean logic map directly onto the math she studied at Clark. She approaches programming problems the same way she approaches proofs: break the problem down, identify the structure, then build the solution step by step.

I'm a recent graduate of the California Institute of Technology in Economics and Computer Science. I was also accepted at Harvard, Princeton, MIT, and Stanford. I have a broad range of interests spanning science, math, engineering, social science, the humanities, the arts, and athletics (I also played on the Caltech basketball team). My background allows me to tutor general college prep, especially the SAT, ACT and the GRE. I love to teach analytical thinking, ranging from advanced Math and Physics to strategies for understanding literature and developing arguments.

I am starting graduate school this fall. My experiences as a student and scientist help me explain concepts and work through problems in a clear and engaging manner. I love teaching, and strive to make each personalized lesson enjoyable and productive. In addition to math and science, I can teach the skills and strategies students need to reach their goals on the ACT, GRE, or AP tests. I also enjoy working with elementary age students to increase reading and math proficiencies.

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.

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.

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.

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.

Justin's PhD research in computational mathematics meant writing code daily — building simulations, implementing algorithms, and debugging in MATLAB and other languages. He teaches computer science concepts like data structures, recursion, and algorithmic complexity by connecting them to real computational problems rather than treating them as abstract definitions to memorize.

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.

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.

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.

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.

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.

I'm trying to work on personal projects. I really enjoy snowboarding, and have been doing that since the third grade. I also enjoy playing sports and video games.

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.