Award-Winning High School Computer Science Tutors
serving San Francisco, CA

Milan's CS degree means he can teach high school programming concepts — variables, control flow, object-oriented basics — with a real understanding of what's happening under the hood, not just pattern-matching syntax from a textbook. His English double major also sharpens how he explains things: he's practiced at making technical ideas readable and clear, which matters when a student is staring at a block of code that makes no sense yet.

The jump from "using computers" to "thinking computationally" trips up a lot of high schoolers, especially when loops and conditionals first appear. Dennis breaks programming logic into small, testable pieces so students build confidence writing their own code instead of copying examples. He holds a 5.0 client rating.

The jump from using a computer to thinking computationally is where most high school CS students struggle. Sarah's training in physics and math gave her deep practice in the kind of logical decomposition that makes loops, conditionals, and basic data structures click rather than feel arbitrary.

I am Chad Bergman, a current Dartmouth student pursuing my Bachelor's in Economics with a physics minor. I have experience tutoring college economics in person on Dartmouth campus as well as online tutoring in high school calculus and physics. I've had great success on the SAT and ACT as well as my AP tests in high school, and I hope to help others succeed as well. My favorite subject to tutor is physics because I feel like learning to apply a few fundamental principles to different real world situations is extremely useful in any discipline. While tutoring I try to help students master the fundamentals so they can apply them to the material we're working on as well as future material. Outside academia, I help look after my four siblings and play more League of Legends online than is perhaps healthy.

I'm a recent college graduate with degrees in Biological Sciences and Russian from Ohio University. During my time there, I tutored students in a variety of subjects, including biology, chemistry, and Spanish. In addition, I worked as both a peer advisor and teaching assistant, which gives me insight into the learning strategies and study skills that students need to succeed. As a tutor, I like to focus on doing actual problems with students because it is the most effective way to immediately identify their strengths and weaknesses and to address them. In my free time, I like to lift weights, read books, and spend time with my friends.

Starting to code can feel overwhelming when a course throws variables, loops, conditionals, and functions at you all at once. William simplifies the learning curve by connecting each concept to a tangible problem — like using a for-loop to simulate a chemical reaction over time — so the syntax has a reason to stick. He scored a 5 on the AP Computer Science exam and brings a patient, step-by-step teaching style rated 4.8 by students.

For students encountering loops, conditionals, and arrays for the first time, the leap from "I followed the example" to "I can solve a new problem" is the hardest part. Anna bridges that gap by teaching structured problem decomposition — breaking a coding challenge into smaller logical steps before writing a single line. Her background spans multiple programming languages, so she adapts explanations to whatever language the course uses.

Between AP Computer Science A prep and general programming fundamentals, Clive covers the full scope of what high school CS courses demand — from writing clean loops and conditionals to understanding recursion and sorting algorithms. He codes in multiple languages and adapts explanations to whatever environment a student's class uses. His approach is to build each concept through small, testable programs so students can see results immediately.

Alicia's architecture degrees from MIT and UT Austin required serious programming — from Python scripts automating structural analysis to Java applications modeling building systems — so she teaches high school CS with a library of real problems, not just textbook exercises. Her Computer Science minor and TA experience mean she can unpack topics like object-oriented design and algorithm logic at whatever depth a student needs. Rated 5.0 by students.

Philosophy trains you to break complex arguments into precise logical steps — which turns out to be exactly what high school CS demands when students hit Boolean logic, nested conditionals, and algorithm design. Julie applies that structured reasoning to programming concepts, teaching students to think through what their code should do before they start typing. Her statistics and machine learning certificate at Princeton means she's no stranger to writing and debugging code herself.

High school CS courses often jump between block-based logic, basic programming, and conceptual topics like binary and networking without much connective tissue. John ties those pieces together by showing how each concept feeds into real software — an approach that makes AP-level material and IB coursework feel less scattered. His CS degree means he can go as deep as a student needs.

Most high schoolers learning to code get stuck not on syntax but on thinking algorithmically — breaking a problem into steps before writing a single line. Nikitha, a University of Michigan CS graduate, tackles that gap directly by teaching students to pseudocode and trace through logic before they touch a keyboard. She covers Java, Python, and core concepts like loops, arrays, and object-oriented design.

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

Most high school CS courses move fast from basic loops and conditionals into more abstract territory like recursion and sorting algorithms, and that's exactly where students tend to lose the thread. Alan's background as both an MIT-trained engineer and a longtime software developer lets him explain why code behaves the way it does, not just what syntax to type.

AP Computer Science and introductory programming courses often trip students up at the same points — loop logic, array manipulation, and understanding how methods pass data around. Michael's UCLA computer science background means he can trace through code line by line and show exactly where a student's reasoning diverges from what the machine actually does. That debugging-oriented approach builds real problem-solving instincts.