Award-Winning Computer Science Tutors
serving Chandler, AZ

From sorting algorithms and Big-O analysis to data structures like trees and hash maps, computer science is ultimately about choosing the right tool for a given problem. Mehek earned her degree in computer and information sciences and teaches across multiple programming languages, which means she can explain concepts at the theoretical level without losing sight of implementation. She's rated 4.7 by students.

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.

I am a graduate student currently working on my Master's Degree in Big Data Systems.

Geoffrey's electrical engineering coursework at ASU means he lives in code daily — from writing embedded C for microcontrollers to building data structures in Python. He tackles computer science as applied problem-solving, connecting abstract concepts like recursion and algorithmic complexity to tangible projects students can see working.

From sorting algorithms and Big-O analysis to database design and operating system fundamentals, computer science covers enormous ground. Ajay brings both an electrical engineering degree and hands-on software engineering experience to the table, which means he can explain not just how an algorithm works in pseudocode but what's actually happening at the hardware level when it runs.

Spencer approaches computer science the way he approaches any complex system: by breaking it into smaller, logical components and understanding how they connect. His analytical training across international relations, business, and quantitative coursework at BYU and Thunderbird gives him a structured problem-solving mindset that translates well to topics like algorithms, data structures, and programming logic. He's especially effective with students who think conceptually but struggle to translate ideas into code.

Concepts like recursion, data structures, and algorithm complexity click faster when someone can show you why a linked list matters, not just how to implement one. Ayushi studied computer science through her master's at Arizona State and spent time tutoring CS students at the university's engineering tutoring center, so she's seen exactly where beginners and intermediate students get stuck. She unpacks abstract ideas with concrete examples and traces through code step by step.

I'm excited to start sharing my love of learning with everyone else.

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.

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.

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.

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.

Allison's CS degree from Dartmouth means she's worked through the full arc — from writing first programs to tackling data structures, algorithms, and computational theory. She unpacks abstract concepts like recursion and Big-O analysis by walking through concrete code examples, making the logic visible before the notation takes over.

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.

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.

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.

Sakibul's graduate work at Rice sits at the intersection of computer science and applied mathematics, which means he tackles programming concepts — loops, recursion, data structures — with the analytical rigor of a mathematician. He breaks down abstract ideas like algorithmic complexity into concrete, step-by-step reasoning that clicks for students encountering CS for the first time.

Isabella TA'd multiple computer science courses at MIT, so she's seen exactly where students get stuck — whether it's tracing recursive calls, understanding how data structures like linked lists and trees actually work in memory, or debugging logic errors in their code. She explains the underlying concepts so that writing correct programs becomes intuitive rather than trial-and-error. Rated 5.0 by students.

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.

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.