Courses & E-Books

Practical stats, plotting, and simple models in Python using real-world datasets.

Learn Python basics + advanced topics.

Recon, exploits, bug bounty hunting. Learn ethical recon, common vulns, Burp workflows, and reporting—without the overwhelm.

A first university level calculus course covering functions, limits, continuity, derivatives, and core applications such as rates of change and optimization.

A continuation of Calculus I focused on definite integrals, techniques of integration, applications to area and volume, improper integrals, sequences, and series.

A multivariable calculus course covering vectors, partial derivatives, gradients, optimization, and introductory vector fields in two and three dimensions.

Double and triple integrals in Cartesian, polar, cylindrical, and spherical coordinates, plus line and surface integrals, Green's, Stokes', and the Divergence Theorem.

A first university-level linear algebra course focused on vectors, matrices, row-reduction and linear systems, with geometric intuition and exam-style practice.

A second linear algebra course on linear transformations, eigenvalues/eigenvectors and inner-product geometry, aligned with a typical Linear Algebra II syllabus.

A capstone third linear algebra course covering the spectral theorem, SVD, conditioning and data-science applications such as PCA and Markov chains.

Logic, sets, combinatorics, and basic proof techniques aimed at CS and security students.

Fourier methods, separation, Green's functions and numerics.

Model, analyze and solve ODEs with theory and computation.

Descriptive statistics, probability basics, and visualizing data for STEM and CS students.

Confidence intervals, hypothesis tests, and simple regression with a focus on intuition and practice.