Award-Winning Computer Science Tutors
serving Lansing, MI

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!

Earning a CS degree from the University of Michigan means Nikitha has worked through everything from data structures and algorithms to systems programming and software design. She teaches concepts through discussion rather than lecture, pushing students to reason through problems like debugging a recursive function or choosing the right data structure for a given task.

I am a junior Computer Science major in the College of Engineering at Cornell University. I have experience tutoring in the National Honor Society in high school, as well as on numerous occasions with acquaintances of mine who were struggling and needed a hand. I tutor high school computer science especially in java and python, as well as algebra (1 & 2) and calculus 1. I love tutoring the math subjects especially, because I feel very comfortable with the subjects and enjoy abstracting them in different ways to help any individual. I believe that success in education is key to building a great life for oneself, and that any person can succeed with the proper work ethic and support network. Even more, I love to see when people I have helped are successful, regardless of area of life. In my spare time, I love to follow college football and basketball and talk about games.

From data structures and sorting algorithms to Big-O analysis, computer science asks students to think about efficiency in a way no other subject does. William's engineering training built exactly that habit: decomposing a complex system, identifying bottlenecks, and optimizing step by step. He connects CS theory to tangible applications so concepts like recursion and linked lists feel intuitive rather than arbitrary.

From writing your first loop to understanding recursion and sorting algorithms, computer science rewards a specific kind of thinking — breaking big problems into smaller, solvable pieces. Nishika earned her CS degree at Michigan and has taught programming in Java, C++, Python, and Scratch to students at very different levels. She adapts her explanations to whether someone needs visual metaphors or wants to dive straight into code.

From sorting algorithms to recursion to Big-O analysis, computer science is really about learning to think in layers of abstraction. Miral's financial math training at Michigan gave her deep comfort with algorithmic logic, and she applies that to teaching students how to design solutions before writing a single line of code.

I'm working towards a B.S. in Physics at Michigan State University with a minor in Computational Mathematics, Science, and Engineering. I've made the Chancellor's List every semester and am a member of my university's Honors College. I've worked with students as young as 11 and as old as 25 for the past couple of years, both online and in-person. Since I'm still a student myself, I can relate to clients and teach in a way that creates a comfortable and safe space. I tutor a broad range of subjects and would love to help you!

Krishanu earned his B.S. in Computer Science and teaches across the full stack — from data structures and algorithms to object-oriented design and recursion. He breaks down abstract concepts like Big-O analysis and memory management into concrete, traceable steps that make debugging and optimization feel intuitive.

I'm a premedical student at Cornell University with extensive experience tutoring students, especially in chemistry at the high school and undergraduate level, writing at the high school and undergraduate level, and SAT/ACT prep.

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.

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.

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.

From data structures and algorithms to computational complexity, Victoria covers the core CS concepts that show up in both coursework and technical interviews. Studying computer science and math simultaneously at WashU gave her a knack for explaining the mathematical reasoning behind topics like recursion, sorting efficiency, and graph traversal. She holds a 5.0 rating from students.

Programming starts making sense when you stop memorizing syntax and start thinking about what the computer is actually doing step by step. June's electrical engineering background at Brown gives her insight into both the hardware and software sides — she can explain why an algorithm is efficient, not just how to write it. From loops and conditionals to data structures and recursion, she connects each concept to real projects she's built in robotics and hackathons.

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.

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.

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.

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.

Philosophy trained Calin to build rigorous logical arguments; his math and CS degrees taught him to express that logic in C++ and JavaScript. That combination means he teaches programming concepts — from algorithm design to data structure selection — as exercises in precise reasoning, where every line of code follows from a clear chain of thought. Rated 5.0 by students.

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.

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.