Award-Winning AP Computer Science Principles Tutors
serving Santa Barbara, 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.

Manideep's day-to-day at Northwestern splits between biology coursework and programming in Python for data analysis, which maps directly onto AP CSP's emphasis on how computing intersects with other fields. He teaches the algorithmic thinking and data representation concepts by tying them to problems he's actually solved — like modeling biological datasets — so the exam's Big Ideas feel grounded rather than abstract. Rated 5.0 by students.

Pratik doesn't come from a traditional CS background, but his premed training at Cornell — where he regularly works with data sets, statistical models, and logical reasoning — maps directly onto the computational thinking AP CSP tests. He's especially effective at breaking down the data analysis and algorithm units, translating abstract pseudocode into the kind of step-by-step problem solving he uses in biology and chemistry every day.

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.

Bryan codes in Java, C++, Python, and JavaScript daily as a CS major at Penn, which means the programming and algorithm design portions of AP CSP come naturally — but he's equally sharp on the conceptual side, like explaining how data travels across the internet or why abstraction matters in system design. He scored a 35 ACT and holds a 5.0 tutoring rating, and he's particularly effective at coaching students through the written response component of the Create Task, where clear technical communication counts as much as the code itself.

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.

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.

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.

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.

I am a current student at the University of Michigan. I am studying molecular biology in the school of literature, science, and the arts. I will graduate in 2025. I am most passionate about teaching SAT test material, because that was an area that I focused on and improved my own score to reach my goals. I am excited to teach both the english and the math sections. I teach using extensive practice problems and practice tests, because that is what helped me learn best and improve my relevant skills. In my spare time I like to workout, swim at the beach, and surf. I would love to work with you to achieve your goals!

Lance studied both theoretical mathematics and computer science as an undergraduate before entering medical school, which means he's written real code in Java, C, and SQL — not just traced pseudocode on a worksheet. That practical depth lets him teach AP CSP's algorithmic thinking and abstraction concepts through actual programming logic, giving students a clearer mental model when they hit the Create Task or encounter unfamiliar algorithm-tracing questions on the exam.

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.

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.