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Siddharth K

Tutor

Joined Apr 2025 · He/Him · 9:06 AM Local

About

Hi! I'm a high school student in Maharashtra, India. I like exploring different areas of math (Algebraic Number Theory and Algebraic Geometry) and cycling in my free time! I'm really excited to learn with others here at Schoolhouse!

Tutor

May 2025 - Present

India

Stats

588

SP

9

Badges

7

Countries Reached

22

Learners Impacted

31

Sessions Hosted

1,894

Tutoring Minutes

Certifications

Algebra 2
100% Mastery
Pre-Calculus
5 / 10 Topics
Calculus
2 / 10 Topics
SAT® Prep
Honorary
SAT Reading & Writing
Honorary

Connections

MD Y
Daniel H
Atsuki Y

Upcoming Sessions

College Linear Algebra Study Group

    5th session

Hi Everyone! Siddharth and Daniel here! This 10 session long bootcamp aims to teach you college-level linear algebra, following MIT's Open Course Ware's Syllabus. Here's the link: https://ocw.mit.edu/courses/18-06-linear-algebra-spring-2010/. This bootcamp won't be too intensive, but at the same time will not be too laid back. We expect to meet twice every week, taking 90 minutes per session. Tentatively, we've scheduled to meet every Saturday and Sunday at 10:00 AM EDT. We will be sure to adjust the timings as per demand! Linear Algebra is essential in reshaping your perspective of the world. You begin to view everything in a form of a vector, matrices, and linear transformations. Linear Algebra plays a fundamental role in understanding key concepts in machine learning and quantum mechanics. Be excited not only to learn more about matrices and vectors, but also about the different real world applications that these concepts can be seen in such as a neat derivation Fourier series - the pinnacle of signal processing - using nothing more than a dash of linear algebra and an elementary fact from a middle school geometry textbook! Enroll now to find out what that is! Algebra 2 and pre-calculus are pre-requisites. While it is not necessary, it would be great if you have exposure to the basic ideas of calculus! Expected Results: 1. Understanding and applying matrix computations and ideas, such as: 2. Solve Ax = b for square systems by elimination. (Including pivots, multipliers, back substitution and more.) 3. Abstract vector spaces, basis and dimension. 4. Orthogonalization by Gram-Schmidt, with the best approximation theorem - a crazy powerful result that allows one to come up with way better polynomial approximations to trig functions than a calculus based Taylor series approach. 5. Eigenvalues and eigenvectors.

Siddharth K and Daniel H

10/20

Featured Feedback

20

great session

Learner · 1 day ago

good

Learner · 6 days ago

Good

Learner · 3 days ago

Thank you for detailed explainations and session!

Learner · 9 days ago

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