A hands-on course for programmers to master Linux daemons: learn how background services work, build your own daemon in C or Python, and manage it using modern Linux tools. Each chapter features practical implementation and real-world system behavior.

Learn how C programs interact directly with the Linux kernel using system calls. This course covers the fundamentals, practical usage, and advanced topics, empowering you to write robust, efficient, and secure Linux applications.

Uncover a complete, practical framework for turning site traffic into measurable growth. You'll start by understanding the psychology behind user decisions, key metrics that signal performance, and the patterns that guide people through a digital journey. Explore advanced optimization techniques including A/B testing, heatmaps, personalization, mobile performance, and iterative improvements. The final modules expand CRO beyond a single page, showing how to optimize full funnels, traffic sources, retargeting flows, and multi-device experiences while building a mindset of continuous experimentation.

Dive deep into the world of SQL query optimization by mastering the EXPLAIN statement and understanding how query planners work. This course blends engaging theory with hands-on, real-world tasks to help you analyze, interpret, and optimize SQL queries using EXPLAIN and related tools.

Gain a rigorous mathematical understanding of neural networks as function approximators. Explore their linear-algebraic structure, approximation power, and the fundamental role of depth in expressivity—without implementation or training details.

A comprehensive theoretical exploration of foundational and advanced network protocols, including TCP, UDP, DNS, TLS, and HTTP/3. This course delves into protocol mechanics, design principles, and deep technical insights, supported by pseudo code and conceptual quizzes.

A rigorous, mathematics-driven exploration of the theoretical foundations, methods, and limitations of neural network compression. This course focuses on intuition, formal reasoning, and the interplay between information theory and deep learning model design.

Understand how Node.js manages asynchronous operations and concurrency through its event loop. Explore callbacks, Promises, and async/await to control complex asynchronous flows with clarity. Apply modern patterns and best practices to write efficient, non-blocking, and resilient JavaScript for real-world Node.js applications.

Explore how Node.js connects event-driven programming with powerful process management tools. Create custom event emitters, manage processes and signals, and control child processes for advanced application workflows. Combine these concepts to design efficient, scalable systems built on Node’s asynchronous architecture.

A beginner-friendly course introducing the core concepts of object-oriented programming in PHP. Learn how to design, implement, and apply OOP principles to build robust and maintainable PHP applications.

Build and manipulate objects to organize data, extend functionality with prototypes, and control context using the this keyword. Apply inheritance, composition, and immutability to write flexible, maintainable code, and use modern techniques like Object.assign and the spread syntax to create clean, efficient object patterns for any project.

Master the mathematical and practical foundations of neural network optimization, explore advanced regularization techniques, and gain hands-on experience with PyTorch and TensorFlow for robust model training.

A comprehensive course for software engineers covering the principles, strategies, and hands-on techniques for performance and reliability testing. Explore the theory behind load, stress, and chaos testing, and learn to apply industry-standard tools and methodologies to ensure robust, scalable, and resilient systems.

Build strong intuition for probability distributions central to machine learning. Explore the exponential family, Gaussian, Bernoulli, and Multinomial distributions, and understand their roles in modeling, loss functions, and inference, with minimal code and clear visualizations.

A beginner-friendly, hands-on course that unravels the mysteries of Python metaclasses. Learn what metaclasses are, how they work, and how to use them to create powerful, flexible, and maintainable code. Each section blends clear theory with practical, real-world tasks to ensure deep understanding.