Award-Winning Computer Science Tutors
serving Santa Ana, 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.

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.

John transitioned from law into co-founding a software company, which meant teaching himself to think in algorithms, data structures, and system design under real deadlines. He approaches computer science the same way — breaking problems into smaller, solvable pieces before writing a single line of code. That builder's mindset makes debugging and logic design feel less intimidating.

From basic programming constructs all the way up to computational analysis and finite automata, Andrew has tutored the full range of computer science topics at both the high school and college level. His CS degree gives him the depth to explain not just how an algorithm works but why its time complexity matters. Rated 5.0 by students.

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.

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.

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.

A Duke CS graduate now pursuing a Master's in Cybersecurity, Noah covers everything from foundational data structures and algorithms to systems-level concepts like memory management and network protocols. He breaks down abstract topics — recursion, Big-O analysis, object-oriented design — by connecting them to real problems rather than leaving them as textbook definitions. Students get someone who's still actively building in the field, not just teaching from notes.

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.

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.