Learn computer science beyond your college syllabus.

C is the language everything else is written in. Learn how memory, pointers and program structure actually work.

C with classes, templates and the STL. The language of game engines, systems and competitive programming.

Readable, batteries-included, everywhere. The fastest path from idea to working code — and the language of data and AI.

The language of enterprise, Android and massive systems. Strong typing, JVM magic and the world's most common job listing.

The language of the web — and now of servers, apps and everything in between. Closures, promises and the event loop made clear.

The single most important subject in computer science. Arrays to graphs, Big-O to DP — the foundation of every technical interview and every serious system.

The four pillars — encapsulation, abstraction, inheritance, polymorphism — plus SOLID design. Language-agnostic and interview-critical.

SQL, transactions, indexing and normalization — how real systems store, protect and query data at scale.

Processes, threads, scheduling, memory and file systems — the software that manages all software.

From HTTP to TCP/IP: how data travels across the world, and how the web really works.

How CPUs execute instructions: the fetch-decode-execute cycle, memory hierarchy and pipelines.

Requirements, architecture, testing, version control and team workflow — how software is actually built in the real world.

The math of countable things: logic, sets, relations, combinatorics, graphs and proofs. The native language of CS theory.

Vectors, matrices and transformations — the math that runs machine learning, graphics and scientific computing.

Uncertainty made precise: random variables, distributions, Bayes' theorem and the laws behind every ML model.

Describing data and drawing conclusions: descriptive stats, inference, hypothesis testing and regression.

Version control for every project you'll ever build — branching, merging, collaborating and undoing mistakes safely.

The structure and style of every web page — semantic markup, layouts, flexbox and grid.

Building interactive interfaces with modern tools: React, state, routing and working with APIs.

Servers, APIs, databases and business logic — the machinery behind every app.

Designing, consuming and testing APIs — REST, JSON, auth, versioning and the tools that make it painless.

The practical half of data: SQL you'll actually write, schema design, indexes and choosing the right database.

The full pipeline from raw data to decisions: collection, cleaning, exploration, analysis and communication.

Algorithms that learn from data: regression, classification, trees, ensembles and the theory behind them.

Neural networks and how they're trained: backpropagation, CNNs, RNNs, transformers and PyTorch.

LLMs, prompt engineering, RAG and building AI-powered products on top of today's foundation models.

Designing systems that handle millions of users: architecture, trade-offs, load balancing, caching and databases at scale.

Multiple machines, one goal: consensus, replication, failures and the algorithms that keep the internet running.

Deploying and running software on AWS/GCP/Azure: compute, storage, containers, serverless and the 'cloud mindset'.

Think like an attacker to defend like an engineer: web security, cryptography, networking attacks and security practice.