Award-Winning Computer Science Tutors
serving Indianapolis, IN

Having a triple major that includes both Computer Science and Mathematics, Darren connects programming concepts to the formal logic and problem-solving frameworks that make them click. Whether it's data structures, algorithm efficiency, or debugging stubborn code, he walks through each problem step by step until the reasoning — not just the syntax — makes sense.

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.

Having TA'd courses in C Programming, Digital Systems Design, and iOS development at Purdue, Akio has debugged student code across enough languages and paradigms to spot the conceptual gaps that cause the most frustration — whether it's misunderstanding pointer arithmetic or struggling with event-driven programming patterns. His computer engineering degree means he teaches software concepts with a hardware-aware perspective, connecting ideas like memory allocation and data representation to what's physically happening on the chip. Rated 4.8 by students.

Christopher approaches computer science as structured problem-solving, breaking down concepts like algorithms, data types, and control flow into digestible steps before ever touching a keyboard. His business analytics coursework at Indiana University keeps him actively coding and thinking computationally, which translates into clear, practical explanations for students just getting started.

I am an incoming college sophomoore studying Aerospace Engineering at the Georgia Institute of Technology. I was one of the top scholars at Carmel High School in Indiana and have various experiences teaching and tutoring through leading the Carmel High School Science Olympiad team to Nationals for two years in a row. Many of my friends consistently come to me for help with various subjects because of my willingness to help and teach in a way that makes sense to everyone. My specialities are physics, chemistry, math, and economics but I am comfortable tutoring any STEM subject, the SAT, and the ACT. Some of my accomplishments include a perfect 36 ACT score, 800 on the Physics, Math Level 2, and Chemistry SAT subject tests, and a 5 on all the physics, Calculus BC, Chemistry, Macroeconomics, Computer Science, etc. AP exams. When teaching, I focus on making sure that not only do students understand different concepts, but also that students understand why and practical applications of the different concepts. As a recent high school graduate, I have a deep understanding of how high-schoolers think, what is covered in various courses now, and can connect with my students a lot more. Additionally, as an undergraduate teaching assistant at the College of Computing at Georgia Tech, I taught weekly recitation sections of 30 students and held weekly office hours. Therefore, I have lots of experience teaching and working with students.

I am currently a sophomore at the University of Notre Dame. I am majoring in Applied Mathematics and Statistics.

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.

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.

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.

Between a master's in Computer Science, an active PhD program, and a full-time software development career, Daniel lives this subject from multiple angles — theoretical and applied. He unpacks everything from algorithmic complexity and data structures to systems-level thinking, tailoring the depth to wherever a student currently sits in their CS journey.

Building AI systems and low-level software at Stanford — in both Python and C++ — Kevin knows where the theoretical meets the practical in computer science. His biocomputation specialization means he can explain not just how to implement an algorithm, but why certain computational approaches work better for different problem domains. Rated 5.0 by students.

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.

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.

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.

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.

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.

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.

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.