Master practical MLOps workflows for deploying, tracking, and maintaining machine learning models in production. Learn to use MLflow, FastAPI, Docker, Airflow, and scikit-learn to automate and scale your ML projects.

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.

Explore the mathematical foundations of mean field theory as applied to neural networks in the large-width limit. Gain a rigorous understanding of distributional perspectives, training dynamics, and the theoretical implications for deep learning.

Create clear, text driven diagrams using Mermaid.js and JavaScript friendly workflows. Learn how to write and embed diagrams, work with multiple diagram types, and customise their appearance for real documentation and web projects.

A theory-first exploration of meta-learning, focusing on mathematical intuition, optimization dynamics, and learning theory. Understand how models learn to learn, the foundations of MAML, and the conceptual landscape of meta-learning methods.

Master the principles and practical techniques for measuring, interpreting, and improving the probabilistic calibration of machine learning models. Learn to use reliability diagrams, calibration metrics, and modern calibration methods to ensure your models produce trustworthy probability estimates.

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 comprehensive, fully theoretical exploration of attention mechanisms in modern neural architectures. This course builds intuition, mathematical understanding, and conceptual clarity around attention, self-attention, multi-head attention, masking, and their role in transformers — without any programming or code.

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.

A rigorous, theory-driven exploration of Neural Tangent Kernel (NTK) theory: infinite-width limits, Gaussian process correspondence, linearized training, kernel dynamics, and the explanatory boundaries of NTK in deep learning.

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.

A beginner-friendly course introducing the essential concepts and practical applications of observability in DevOps. Learn how logs, metrics, and traces provide visibility into systems, how to use dashboards and alerts, and how to interpret service health using SLIs and SLOs. Each chapter combines clear explanations with real-world text-based examples to build foundational skills for modern DevOps workflows.

A comprehensive, hands-on course exploring the theory, intuition, and practical implementation of outlier and novelty detection algorithms in Python. Learn to identify anomalies using statistical, isolation, density, and kernel-based methods, interpret results, and compare approaches for real-world applications.

Dive deep into PHP's Foreign Function Interface (FFI) internals. Learn how PHP interacts with native C code at runtime, how memory and types are managed, and what performance and security implications arise. This course is designed for experienced PHP developers with a basic understanding of C.

Learn how to build your own MVC architecture step by step using only native PHP. This course guides you through the core concepts and practical implementation of the Model-View-Controller pattern, empowering you to create scalable and maintainable PHP applications without relying on frameworks.