Award-Winning AP Computer Science Principles Tutors
serving Queens, NY

Stanford's economics curriculum leans heavily on data analysis and programming — skills that map directly onto AP CSP's units on data representation, algorithms, and computational thinking. Julia applies that quantitative training to demystify pseudocode logic and the Create Task's written responses, where clearly explaining your program matters as much as building it. Rated 4.8 by students.

Nicholas codes in Java, Python, JavaScript, C#, and HTML/CSS daily — so when AP CSP asks students to reason about algorithms or data representation in pseudocode, he can instantly translate those abstractions into real programming scenarios that make the logic click. His Penn State CS degree also means he understands the networking and cybersecurity concepts woven through the course at a technical level most high schoolers never see. Rated 5.0 by students.

John's CS degree plus years coding in Java, C++, and SQL means he can ground AP CSP's more abstract units — like how the internet actually moves data or why abstraction matters in program design — in real programming experience. He also brings a finance MBA perspective to the data analysis and societal impact questions, giving students a practical lens that makes exam responses sharper and more specific.

Currently studying Computer Science at UCLA's Engineering School with a software engineering internship at Adobe under his belt, David knows how the abstractions taught in AP CSP — algorithms, data representation, internet protocols — actually play out in production code. He uses that industry context to make pseudocode tracing and the Create Task feel purposeful rather than academic. Rated 4.8 by students.

Susanna codes in Java, Python, and MATLAB — but for AP CSP, she shifts gears from syntax to the bigger questions: how does data move across the internet, why does abstraction matter, and what makes an algorithm efficient? Her physics training at UC Berkeley means she's used to translating messy real-world problems into clean logical models, which is exactly the skill the Create Task and exam reward.

Mathematics trains you to think in abstractions — which is exactly what AP CSP's Big Ideas demand when students encounter data representation, algorithmic logic, or internet protocols for the first time. Nikhil's math background at NYU gives him a natural framework for making pseudocode tracing and binary concepts click, especially for students who think numerically but haven't written much code. Rated 4.8 by students.

I'm a professional software engineer at a top tech company in New York City. I have a strong passion for software development, most notably in the areas of full-stack web development, iOS development, Artificial intelligence, large scale distributed systems, and micro services.

I am a sophomore at Columbia University, studying political science and philosophy. I often like to joke that teaching runs in my blood I come from a family of teachers who instilled in me the passion to help others learn. Since I could grasp concepts I learned in school, I've always gone out of my way to help my fellow classmate. As I got older, that became formalized tutoring through school organizations and I eventually worked for the New York City Department of Education. There, I helped students with their standardized testing for the state assessments and the SAT. I love teaching math because I feel it's the subject where I can gauge the strength of my students best. Math is such a versatile (though widely-hated) subject, where every unique learning style can always result in the same answer. I also get the most freedom when it comes to designing questions to help students grow and practicing alongside them easily the most fun part of a tutoring session with me. I'm never shy when it comes to tutoring anything else, though, whether it be any sort of history, literature, or government-related topic. My goal as a tutor is not all about teaching anything new to my students, but instead drawing out the skills they already have.

Before teaching AP CSP concepts, Deeptha spent years as a TA for courses ranging from Introduction to Computation in Python to Automata and Formal Languages — meaning she's watched hundreds of students encounter computational thinking for the first time and knows exactly where confusion sets in. She uses that experience to break down the course's Big Ideas around the internet, data, and global impact into concrete examples students can actually write about on the exam.

Kyle knows six-plus programming languages — Python, Java, C++, JavaScript, C, and assembly — which means when AP CSP's exam asks students to trace pseudocode or reason about abstraction, he can pull up a real example in whatever language makes the concept clearest. He also walks students through the Create Task from initial brainstorm to written response, making sure every rubric point is addressed. Rated 5.0 by students.

Nihar's math and statistics degree means the data analysis and algorithmic reasoning threads in AP CSP come naturally — he can explain how sorting algorithms compare or why a particular data compression method loses information, grounding it in the quantitative thinking most students skip over. His programming experience across Java, JavaScript, SQL, and HTML also lets him translate pseudocode exam questions into real code when a student needs to see the logic in action.

AP CSP covers a mile-wide range — from binary and abstraction to the impact of computing on society — and the Create Task alone can make or break a student's score. Serina's computer science major at Yale means she can demystify concepts like data compression, algorithms, and the internet protocol stack while coaching students to write clean, well-documented code for their performance tasks.

Shlomo codes in Java and C++ and has tutored algorithms at the college level, so he can ground AP CSP's pseudocode and algorithmic reasoning questions in actual programming logic rather than hand-wavy definitions. His political science training also sharpens the kind of structured argumentation the Create Task's written responses demand — explaining computational decisions clearly and hitting every rubric point.

Payton is a Computer Science major at Texas A&M who codes in Python, C++, and Haskell — but AP CSP's exam cares more about pseudocode reasoning and explaining computational ideas in plain English than writing compilable programs. She teaches students to bridge that gap, translating real programming instincts into the kind of clear, structured responses the Create Task and multiple-choice questions actually reward. Rated 4.9 by students.

I'm always up for the challenge of changing my methods of instruction and breaking down topics to foster a deeper understanding of a subject. On a different note, I generally spend my spare time playing lacrosse or running outdoors when possible. I also play the violin with a school quartet, and teach lessons to beginning students working through the Suzuki program.

Irene's PhD in Mathematics and Computer Science means she understands the computational thinking that underpins AP CSP — not just the vocabulary, but the discrete math and logic behind how algorithms work and why abstraction matters. She unpacks pseudocode problems by connecting them to the mathematical structures students rarely see in a survey course, which makes exam questions feel less like guesswork.

Teaching discrete math at Penn means Keenan spends his weeks translating abstract computational thinking into language undergraduates actually absorb — a skill that maps directly onto AP CSP's pseudocode reasoning and algorithm analysis questions. His philosophy degree also gives him an unusual edge on the exam's societal-impact questions, where students need to construct clear written arguments about data privacy, bias in algorithms, and computing ethics. Rated 5.0 by students.

I am graduated from Penn State University in Industrial Engineering in 2017. I've tutored ever since I was in high school, and I love helping people! I like to help my students understand math (and other topics) instead of just doing it blindly. My goal is to help my students improve their math (and other topics) and build skills that will help them find learning easier in the future! Fun fact, I used to work for Disney and I like to salsa dance!

Most AP CSP students get tripped up not by the technical content but by the exam's pseudocode — reading and tracing algorithms written in a language nobody actually codes in. Maxwell's math and physics training means he thinks naturally in abstractions and logical structures, so he can teach students to parse those pseudocode questions the way he'd parse a proof: step by step, tracking what changes and why. Rated 5.0 by students.

Software engineering internships at Apple and Microsoft gave Jerry a firsthand view of how the concepts in AP CSP — abstraction, algorithm design, data representation — actually play out in production code. He uses that industry context to make the Create Performance Task feel like a real development project rather than a classroom exercise, which sharpens both the programming and the written-response components. Rated 4.9 by students.

JF studies mathematical and computational science at Stanford, which means the algorithmic thinking and data representation ideas in AP CSP are woven into his daily coursework — not abstract exam topics. He teaches students to reason through pseudocode problems and structure their Create Task projects so every rubric criterion is addressed with clarity. Rated 5.0 by students.

Victoria's CS coursework at Washington University in St. Louis means she can ground AP CSP's abstract Big Ideas — like how abstraction layers simplify complex systems or why algorithms have different efficiencies — in actual programming experience across Java, Python, and C++. That real coding fluency is especially useful when students need to move from pseudocode on the exam to functional code in the Create Task. Rated 5.0 by students.

Intensely curious, I am interested in STEM subjects and the liberal arts. I tutor to help you reach your educational goals and because it's immensely gratifying to see my students succeed.

Adel's PhD in mechanical engineering required extensive work in Java and computational modeling — skills that translate directly to the algorithmic thinking and pseudocode analysis at the heart of AP CSP. He unpacks topics like data representation and abstraction by tying them to engineering simulations where those concepts have real consequences. Rated 4.8 by students.

Six semesters as a teaching assistant for digital logic at Cornell gave Alexander a deep intuition for how computers actually think — the binary, the abstraction layers, the logic gates underneath every algorithm. He brings that hardware-level understanding to AP CSP's big ideas, especially when explaining how the internet and data representation work under the hood. Rated 5.0 by students.