Award-Winning AP Computer Science Principles Tutors
serving Manhattan, 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.

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.

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.

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.

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.

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.

Ritesh's physics training at Cornell actually maps neatly onto AP CSP — both demand thinking about systems in layers, whether that's abstraction in computing or modeling forces in mechanics. He teaches the pseudocode and algorithm-tracing portions by treating them like physics problem-solving: break the system into parts, track what changes at each step, and verify the output makes sense.

Miguel's dual CS and English degree is a rare combination for AP CSP, where half the battle is writing code and the other half is explaining it — the Create Task's written responses demand the same clarity and structure as a well-argued essay. He teaches students to translate their algorithmic thinking into the precise language the rubric rewards, bridging the gap between understanding abstraction and actually articulating it on paper. Rated 4.9 by students.

Studying neuroscience at Rice means Brett regularly writes code to analyze brain imaging data and model biological systems — practical computing experience that maps directly onto AP CSP's emphasis on data analysis, algorithms, and the real-world impact of technology. He teaches the pseudocode logic and abstraction concepts the exam tests by grounding them in problems students can actually picture. Rated 5.0 by students.

AP CSP's exam leans heavily on the impact-of-computing and internet-infrastructure Big Ideas that many tutors rush past in favor of pseudocode drills. Alston's CS coursework at UVA gives him the technical grounding to teach those systems-level topics thoroughly, while his background in writing and essay editing makes him a strong coach for the Create Task's written response — the piece most students underestimate until it costs them points.

Nikitha earned her CS degree from Michigan writing actual code — which gives her a practical lens on AP CSP's more conceptual terrain, where students often stumble because the material feels too broad to pin down. She zeroes in on the impact-of-computing and cybersecurity threads that many tutors gloss over, tying them back to real design decisions she encountered in her own coursework. 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!

Samuel's applied math training at Caltech intersects directly with AP CSP's algorithm and data units — he can trace how a sorting algorithm's efficiency scales or why lossy compression works because he uses that math daily. He also taught a discrete mathematics course through PACT, which means pseudocode logic and combinatorial reasoning come naturally when prepping students for both the multiple-choice exam and the Create Task.

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.

Two years working in AI and machine learning gave Brandon a firsthand sense of how the Big Ideas in AP CSP — data representation, algorithmic efficiency, the societal implications of computing — play out in industry, especially around bias in datasets and the ethics of automation. He teaches the Internet and cybersecurity portions of the course through the lens of systems he's actually built, and his CS master's work at RIT keeps him sharp on the pseudocode reasoning the exam demands. Rated 4.9 by students.

Cindy doesn't come from a traditional CS background, but her 36 ACT and analytical training as a Harvard English student give her a sharp edge on AP CSP's most underestimated challenge: the written responses. The Create Task and exam both reward students who can explain computational ideas — abstraction, algorithms, data patterns — in clear, precise language, and that's exactly the skill set she brings to every session.

Firas's machine learning research at Princeton means he can show students what abstraction, algorithms, and data representation actually look like in practice — not just as AP exam vocabulary but as tools working scientists use daily. He's particularly sharp at teaching the pseudocode reasoning and written response skills the Create Task demands, since his PhD work required translating complex computational ideas into clear, precise language. Rated 5.0 by students.

Ronit studies computer science at Yale and knows AP CSP's curriculum from the student side — which Big Ideas actually trip people up on the multiple-choice and where the Create Task rubric quietly punishes vague written responses. He digs into the explanatory writing piece that most students underestimate, teaching how to describe an algorithm's purpose and trace through pseudocode with the precision the exam expects. Rated 5.0 by students.