Software & AI Engineering
From core fundamentals and algorithms to autonomous AI systems
Operating Systems
How one machine runs thousands of programs at once: system calls, processes and threads, scheduling, virtual memory, locks and deadlock, file systems, I/O and containers.
Networking Concepts
Core protocols and architecture covering OSI & TCP/IP layers, routing, DNS, sockets, HTTP/3, and network security.
Programming Languages
Comprehensive study guides covering language syntax, data structures, OOP, closures, asynchronous runtimes, memory models, and execution internals.
DSA
Visual explanations, real-world mental models, algorithmic paradigms, complexity analysis, and interview problem solutions.
Git
Distributed version control workflows: staging, branching & merging strategies, interactive rebasing, merge conflicts, and team collaboration.
DevOps
Developer-centric containerization and deployment workflows: Docker packaging, Kubernetes app runtime, CI/CD pipelines, 12-factor config, and app observability.
AWS
Developer-centric cloud engineering: EC2, ECS & EKS containers, serverless Lambda, S3, DynamoDB single-table design, VPC subnets & Well-Architected systems.
AI Projects
Hands-on AI applications, LLM orchestration, RAG pipelines, autonomous agents, and interview evaluation tools.