Award-Winning AP Computer Science Principles Tutors
serving Los Angeles, CA

Caltech's CS curriculum drills computational thinking at a level that makes AP CSP's big ideas — abstraction, algorithm design, data representation — feel like familiar territory for Brian. He teaches students to reason through pseudocode and explain their design choices in plain language, which is exactly what the Create Task and the multiple-choice exam reward. His 1580 SAT speaks to the kind of precise, analytical communication that carries across disciplines.

The AP CSP exam's multiple-choice section leans heavily on reading comprehension — interpreting pseudocode, parsing scenario descriptions, and eliminating wrong answers under time pressure. Dennis's communication background makes him unusually good at teaching students to slow down and decode what a question is actually asking before jumping to an answer. Rated 5.0 by students.

Biomedical engineering at Cornell means Annie writes Python and MATLAB to process real research data — skills that map directly onto AP CSP's emphasis on programming, data analysis, and algorithmic thinking. She teaches the Create Task as a scaled-down version of the same design process she uses in lab: define the problem, plan the logic, build iteratively, then explain your choices clearly. Rated 4.9 by students.

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 a recent graduate with a master's in electrical engineering from Case Western Reserve University. I won the Bill and Melinda Gates Millennium Scholarship which covers full tuition up to Ph.D. I was on the Dean's List for three consecutive years. Additionally, I won the OZY Media Genius Award in 2015 to work on high-temperature superconductors. I currently work as a Technology Analyst at Accenture. I am also seriously considering whether I should go for a Ph.D. or not.

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.

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.

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.

Studying Computer Science at UNC Chapel Hill, Jack brings hands-on programming experience in Java and C to a course where most students are writing their first real program for the Create Task. He digs into the pseudocode logic and algorithm design questions that trip up students on the multiple-choice section, connecting them back to actual coding patterns so the reasoning clicks. Rated 4.7 by students.

Daniel writes production software for a living and is pursuing a PhD in Computer Science, which means he can show students exactly how concepts like abstraction, algorithms, and data representation play out in real codebases — not just on slides. He's particularly effective at coaching the Create Task, walking students through project planning and the written responses that separate a 3 from a 5. Rated 5.0 by students.

Most AP CSP students get tripped up not by the coding but by the Big Idea questions that ask them to reason about how computing affects the world — privacy, bias in algorithms, digital divide issues. Susie pairs her Duke CS coursework with a genuine interest in the humanities side of tech, which means she can coach students through both the conceptual exam material and the written responses on the Create Task without defaulting to jargon.

Robotics engineering at WPI means Matthew writes code that has to actually control physical systems — sensors, motors, feedback loops — which gives him a practical lens on AP CSP's units on algorithms, abstraction, and data representation. He teaches the pseudocode reasoning behind exam questions by tying each concept back to how real machines process information. Rated 5.0 by students.

Kevin's Stanford Biocomputation research sits at the intersection of CS and biology, which means he can teach AP CSP's algorithmic thinking and data analysis concepts through real examples — like how machine learning models process biological datasets or how compression algorithms handle genomic sequences. He also brings hands-on Python and C++ fluency to the Create Task, coaching students through both the programming and the written explanation that the rubric demands. Rated 5.0 by students.

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.