General

Master discrete mathematics through hands-on Python. Covers sets, functions, logic, Boolean algebra, induction, recursion, graphs, trees, relations, and combinatorics — every concept paired with runnable code and interactive simulations. Build Dijkstra's algorithm from scratch, wire up logic gate circuits, step through recursive call stacks, and drag elements across Venn diagrams. 20 lessons, 7 interactive visualizers, and graded exercises that test both mathematical reasoning and implementation skill.

IELTS Band 7+ for Software Engineers cuts through the noise of generic preparation courses. This course assumes you can already read technical documentation, write professional emails, and hold a conversation in English — so it skips grammar 101 and gets straight to exam mechanics. The IELTS is not an English test. It is a test of whether you know the rules of the IELTS. This course decodes those rules: double paraphrasing in Listening, the False-vs-Not-Given distinction in Reading, the development rule that separates Band 6 from Band 7 in Writing, and the 45-second outline technique that determines your Speaking score before you open your mouth. Built from an analysis of 90,000 lines of transcribed instruction from a Udemy bestselling IELTS course (15+ years of examiner-level teaching), scored student mock tests from 10+ countries, and direct examiner feedback. Engineer-specific failure modes — robotic delivery, terse answers, topic-writing instead of question-answering, perfectionism stalls — are addressed explicitly in every module. Designed for Band 7+ targets. Contains everything a technically fluent English speaker needs to crack the exam in 2–4 weeks of focused preparation.

Over two weeks, go from finding everyday problems worth solving to building a complete business plan and pitching it like a pro. You'll create customer personas, calculate market sizes, design business models, crunch revenue and profit numbers, assemble dream teams, and craft pitch decks, all through hands-on interactive tools. Cap it off by pitching your startup idea to an AI investor who asks tough follow-up questions and decides whether to invest.

Master the five stages of design thinking: Empathize, Define, Ideate, Prototype, and Test. Through seven hands-on interactive tools, you'll build empathy maps, craft problem statements, brainstorm on digital canvases, wireframe app screens, map user journeys, organize feedback, and run A/B test experiments, practicing the same methods used by professional designers at companies like Apple, Google, and IDEO.

Go from curious beginner to confident AI explorer in five weeks. You'll discover how machines learn from data, build your own training sets, watch neural networks process information in real-time, master prompt engineering for generative AI, and tackle big ethical questions about bias, accountability, and fairness. Every concept comes alive through interactive simulations where you experiment, break things, and build understanding by doing. No prior AI experience required, designed for ages 10-16.

Become a data detective over five weeks: master mean, median, mode, and range, collect clean data, build stunning charts, spot trends and correlations, train a simple machine learning classifier, and present your findings as a compelling data story. Every concept comes with hands-on interactive tools where you build visualizations live and practice the same skills used by real data scientists, journalists, and business analysts.

A hands-on 10-week journey through programming fundamentals and algorithmic thinking using Python, designed for learners aged 10-16. You'll build a solid foundation in variables, operators, conditionals, loops, and functions, then dive into recursion, sorting algorithms, graph theory, and Dijkstra's pathfinding. Every concept comes alive through interactive apps like a Variable Explorer, Sorting Visualizer, and Caesar cipher encoder.

Learn to think like a computer scientist without writing a single line of code. Over five weeks, you'll master problem decomposition, abstraction, pattern recognition, algorithmic thinking, and logical reasoning through interactive puzzles, visual simulators, and hands-on challenges like Pascal's Triangle, the Tower of Hanoi, sorting algorithm races, logic circuits, and a multi-stage treasure map puzzle. Designed for learners aged 10-16.

The SIM-Reporting-Service is a TypeScript/Node.js report generation engine built on Azure Durable Functions. It processes report requests from a Service Bus queue, fetches data from SQL Server, renders PDF and CSV reports using EJS templates and Playwright Chromium, stores them in Azure Blob Storage, and publishes notifications for email delivery via the downstream SIM-Telemetry-JS notification service. This course provides a comprehensive deep dive into the SIM-Reporting-Service and its place within the broader SIM platform. You will learn the event-driven microservices architecture connecting SIM-Telemetry (.NET), SIM-Reporting-Service (Node.js), and SIM-Telemetry-JS (Node.js), including the four-factory pipeline design, Durable Functions orchestration, and Service Bus messaging patterns. Beyond architecture, the course covers practical operational knowledge: end-to-end data flows, error handling and retry behavior, security architecture with dual-layer PII encryption, CI/CD deployment pipelines, incident response runbooks, and the testing strategy. You will also learn how to extend the system by adding new report types and notification types, set up local development environments, and diagnose common production failures. Whether you are onboarding to the team, preparing for on-call duties, or deepening your understanding of Azure-based IoT reporting systems, this course equips you with the knowledge to work confidently with the SIM-Reporting-Service.

A comprehensive course on the SIM-Telemetry-JS notification delivery engine for the SIM IoT platform. This service, built with TypeScript and Node.js on Azure Functions v2, implements a fan-out pattern to deliver notifications via Email (SendGrid), Push (Firebase FCM), and WhatsApp (Graph API) across 100+ notification types. You will learn the full architecture spanning three microservices (SIM-Telemetry .NET, SIM-Telemetry-JS, and SIM-Reporting-Service), including the three-level factory pattern, Redis caching with AES-256-CBC encryption for PII, and the shared SQL Server database schema. The course traces end-to-end data flow from IoT device telemetry through Azure Service Bus queues and topics to final notification delivery. Beyond architecture, this course covers practical operational knowledge: infrastructure and deployment on Azure, CI/CD pipelines, local development setup, how to add new notification types, and production runbooks for incident response. You will also learn the testing strategy, integration test patterns, and known technical debt items that affect the system's reliability and security.

A comprehensive course covering the SIM-Telemetry platform — the core IoT telemetry processing engine built on .NET 8 Azure Functions. This course walks through the complete system architecture spanning three microservices: SIM-Telemetry (C# data ingestion and orchestration), SIM-Telemetry-JS (Node.js notification delivery), and SIM-Reporting-Service (Node.js report generation). You will learn how device telemetry flows from 40+ IoT device types through Azure IoT Hub, gets parsed and processed by a Durable Functions orchestrator with 11 parallel activities, and results in real-time dashboard updates, threshold notifications via Email/Push/WhatsApp, and automated PDF/CSV report generation. The course covers the data ingestion pipeline, the three-tier caching strategy, the factory method patterns used throughout, and the Service Bus queue-to-topic fan-out architecture for notification delivery. Beyond architecture, this course covers operational concerns: database schema ownership across services, PII encryption with defense-in-depth, feature toggles for production control, incident response procedures, and known technical debt. Whether you are onboarding as a new engineer or deepening your understanding of the platform, this course equips you with the knowledge to contribute effectively.

Master the four pillars of computational thinking (decomposition, pattern recognition, abstraction, and algorithm design) through real engineering scenarios like system design, production debugging, and technical decision-making. You'll learn to model systems using graphs, state machines, sets, and recursion, and develop systematic approaches to problem framing, estimation, and tradeoff analysis. This is not an algorithms course; it's a thinking course that gives you structured frameworks to cut through ambiguity and make better engineering decisions faster.