Courses

Yaser Abu-Mostafa's famed Caltech course on statistical learning theory: Hoeffding's inequality, VC dimension, bias-variance tradeoff, regularization, support vector machines, and neural nets.

Martin Kleppmann's concise Cambridge lecture sequence on physical and logical clocks, causality, broadcast protocols, Raft consensus, replication, CRDTs, and distributed transactions.

Inside modern relational and analytical DBMS internals: relational algebra, slotted-page storage, log-structured merge trees, columnar compression, buffer pool management, and hash/B+Tree indexes.

Rigorous introduction to computability and complexity theory, covering Turing machines, diagonalization, NP-completeness, space complexity, Savitch's theorem, and the polynomial hierarchy.

Graduate systems seminar on modern OLAP execution engines: columnar compression, Parquet/Arrow formats, vectorized SIMD execution, JIT query compilation, worst-case optimal joins, and cloud lakehouses.

Advanced systems course on relational query optimization, analyzing System R bottom-up dynamic programming, Volcano/Cascades top-down rule engines, cardinality estimation, and join ordering.

Intensive PhD-level complexity theory sequence examining circuit complexity, randomized computation, interactive proofs, PCP theorem foundations, pseudorandomness, and hardness amplification.

Research-level course developing Fourier analysis over the Boolean hypercube, hypercontractivity, noise stability, invariance principles, and applications to hardness of approximation and social choice.

Mathematical development of quantum circuits, entanglement, quantum query complexity, phase estimation, Shor's factoring algorithm, quantum channels, and quantum error correction.

State-space dynamical systems, stability eigenvalues, controllability, observability, Linear Quadratic Regulators (LQR), and Kalman filtering derived for modern control engineering.

Flows on the line and circle, saddle-node and pitchfork bifurcations, two-dimensional phase planes, limit cycles, Hopf bifurcations, Lorenz equations, strange attractors, and fractals.

Cross-disciplinary course at ETH Zürich examining high-throughput genome sequence analysis, read mapping algorithms, graph genomes, and hardware acceleration for bioinformatics.

From CMOS transistors, combinational logic, and sequential state machines up through instruction set architectures, pipelining, out-of-order execution, caches, DRAM controllers, and hardware accelerators.

Harvard's flagship introduction to algorithmic thinking and systems programming: C pointers and memory layout, data structures, Asymptotic complexity, Python, SQL relational schemas, and web security.

Applies administrative tax, education, and census datasets to intergenerational mobility, neighborhood effects, innovation, health disparities, and tax policy.

Michael Sandel's landmark moral and political philosophy course examining Bentham, Mill, Nozick, Locke, Kant, Rawls, and Aristotle through live Socratic courtroom and policy dilemmas.

Harvard's celebrated probability sequence building story proofs, conditioning, Bayes' theorem, indicator random variables, continuous distributions, moment generating functions, and Markov chains.

Dedekind cuts construction of the reals, metric space topology, compactness, Heine-Borel theorem, connected sets, Cauchy sequences, uniform continuity, and function spaces.